Welcome to our training catalog. All courses are provided in-house and the courses listed below can be mixed to meet your needs.

Please contact us to discuss what courses would best match your requirements and if you have any questions on specific courses or course categories.

 

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Data Strategy and Governance
List of courses that address Data Strategy and Governance with a focus on GOC Digital Strategy.
Developing a Data Strategy Roadmap
Developing a Data Strategy Roadmap Image

In the recent Privy Council report “A Data Strategy Roadmap for the Federal Public Service”, a roadmap was laid out for GOC Departments to create Data Strategy and Governance frameworks and to implement them through a robust Data Strategy Roadmap.

This module investigates the impact this has on GOC Departments, and, more importantly, on the groups and lines of business within those Departments.

We provide guidance and recommendations derived from widespread best practices on how Senior Executives and Managers can design and implement activities to:

  • create an internal roadmap to implement Departmental Strategy and Data Governance
  • establish a decision making group to enforce departmental mandates including accountabilities, roles and responsibilities
  • identify key roles and responsibilities around data leadership
  • understand ethical and secure use of data
  • assess the current state of data literacy, skills and competencies
  • establish good hiring practices
  • review and update data training and development strategies
  • understand departmental policy frameworks and how they affect the group / line of business
  • assess infrastructure needs
  • help foster innovation through pilot projects
  • develop a data quality framework
Product Code: DC-1
Course Duration (hours): 4
Developing a Data Governance Strategy
Developing a Data Governance Strategy Image

This module aids participants with the practical implementation of a Data Governance Strategy.

All GOC Departments are now, at a high level, developing Data Strategies to align with the Privy Council report “A Data Strategy Roadmap for the Federal Public Service”, but how does this affect individual groups within GOC Departments, Agencies and Crown Corporations?

In this module, you will learn the key principles and best practices that drive Data Strategy and how they can be practically implemented in the workforce to provide a positive return on investment through key data practices, including how to:

  • identify data needs and strategies for alignment with departmental strategy
  • assess, review and address the needs of stakeholders
  • be an ongoing champion of data use
  • use data to guide decision making
  • effectively prepare to share data both internally and externally
  • obtain key insights from data
  • use data to review and enforce accountability and responsibility
  • connect data functions internally across groups and externally with OGD and 3rd parties
Product Code: DC-2
Course Duration (hours): 4
Data Strategy and Governance Checklist Review
Data Strategy and Governance Checklist Review Image

This module uses the information provided in DC 1 Developing a Data Strategy Roadmap and DC 2 Developing a Data Governance Strategy and walks participants through a pre defined checklist to assess where their Department, Group or Line of Business finds itself in relation to GOC and Departmental expectations.

Upon completion, the participants will have an understanding of where their GAPs are and have the ability to perform a more comprehensive analysis to come up with an action plan to close the GAPs.

Product Code: DC-3
Course Duration (hours): 4
Empowering a Data Focused Workplace
Empowering a Data Focused Workplace Image

This module provides tips and approaches to help empower a data focused workplace. It is not sufficient to rely on a small number of individuals to manage and use data – all employees need to understand their role in the creation, analysis, dissemination and curation of organizational data. in this module, you will learn how to:

  • create a data based decision culture where the fundamental objectives are collection, analysis, and deployment of data to make better and more informed decisions
  • understand the tools that allow the workforce to enhance their analysis and decision making skills
  • understand what specific data training & development is required to up skill the workforce
  • recognize the data competencies that are required to run a standard data workplace
  • establish the importance of democratizing data, or how to get the right data in front of the right people at the right time
  • deploy dynamic risk management in everyday data driven decision making
  • find and empower your organization’s data evangelists
  • build a reliable and consistent data management process
Product Code: DC-4
Course Duration (hours): 4
Analyzing Data to Identify Improvement Activities
Analyzing Data to Identify Improvement Activities Image

This module investigates methods to link the results of data analysis with departmental or group objectives. The standard is often “analysis for the sake of analysis”. In this module, we show how to build an analysis framework that aligns with departmental and group objectives. Participants will learn:

  • how to precisely articulate business objectives
  • to identify what type of analysis will measure the business objective
  • how do define what data is required to build the analysis models
  • how to monitor the analysis over time and make the linkages between analytics and objectives
  • how to take analysis results and make meaningful recommendations
Product Code: DC-5
Course Duration (hours): 4
Initiating and Managing AI/ML Projects I
Initiating and Managing AI/ML Projects I Image

This is the first of three modules on running Artificial intelligence (AI) and Machine Learning (ML) projects. Compared to regular projects, these project categories typically require a different approach to set up and run. Due to the significant amount of discovery required in AI/ML applications, standard project management frameworks such as PMBoK and Prince2 (or similar) phased approach usually need to be modified to ensure project success. in the first of these modules, you will learn:

  • what makes AI/ML projects different
  • how to define requirements for AI/ML projects
  • the importance of research and discovery as managed phases of project implementation
  • new skills required of project managers
  • critical roles in the implementation of AI/ML projects
Product Code: DC-6
Course Duration (hours): 4
Initiating and Managing AI/ML Projects II
Initiating and Managing AI/ML Projects II Image

This is the second of three modules on running Artificial intelligence (AI) and Machine Learning (ML) projects. in this module, you will learn:

  • how to understand AI/ML infrastructure requirements
  • AI/ML techniques trade off in relation to project requirements
  • initial and ongoing risk management
  • model management and prioritization
  • quality control and assurance activities
  • ongoing system management and maintenance
Product Code: DC-7
Course Duration (hours): 4
AI/ML Projects: Case Study Workshop
AI/ML Projects: Case Study Workshop Image

The third and final module in our Artificial intelligence (AI) and Machine Learning (ML) project series. in this module, participants are presented with a series of case studies which are analyzed to derive lessons learned and best practices. The module also provides an opportunity for participants to present information on their own projects for the group to review and provide feedback.

Product Code: DC-8
Course Duration (hours): 4
Data Roles: Who to Hire in the information Workplace
Data Roles: Who to Hire in the information Workplace Image

In a dynamically changing workplace, it is difficult to understand what new and changing roles are required to build a data focused workplace. in this module, we outline some of the key new roles that may be required and what competencies each role requires. This will aid in the selection, hiring, development, and training of data employees, helping to provide maximum benefit to the organization and growth opportunities for the employees.

We cover several data roles, and take a closer look at competencies, roles and responsibilities for:

  • domain experts
  • data translators
  • data engineers
  • data scientists
  • analysts (data and business)
  • computer scientists
  • computer engineers
  • AI/ML QC specialists
Product Code: DC-9
Course Duration (hours): 4
Data Toolbox Overview I (self service tools)
Data Toolbox Overview I (self service tools) Image

The first of two modules providing an overview of standard software tools. This module looks at self service tools including (other tools may be included at the discretion of Data Action Lab or by request):

  • Code based analysis tools
  • Data visualization and Business Intelligence tools
  • Data engineering tools
  • Simulation and symbolic mathematical tools
  • Statistical packages
Product Code: DC-10
Course Duration (hours): 4
Data Toolbox Overview II (enterprise tools)
Data Toolbox Overview II (enterprise tools) Image

The second of two modules providing an overview of standard software tools. This module looks at enterprise tools, including tools provided by (other tools may be included at the discretion of Data Action Lab or by request):

  • Google
  • Microsoft
  • IBM
  • SAS
  • ESRI
Product Code: DC-11
Course Duration (hours): 4
A Manager’s Guide to Data Engineering
A Manager’s Guide to Data Engineering Image

A department’s data analyses are only as good as the data that they access. Essentially, data engineering is the creation of data pipelines that enable the data scientists and analysts to do their work properly. As the workplace becomes more data focused, data engineering is moving from its traditional home in the IT department and directly into business lines. This module will give participants and overview of what data engineers do and how critical data pipelines are.

Participants will learn:

  • the importance of a well designed data pipeline
  • strategies for aggregating and combining data sources
  • Treasury Board Secretariat guidelines and milestones in the storage and communication of Protected B (and high level) information
  • what tools data Engineers need access to
  • approaches to data collection and validation
Product Code: DC-12
Course Duration (hours): 4
Black Books: Identifying and Managing Rogue Data Sources
Black Books: Identifying and Managing Rogue Data Sources Image

All groups within GOC Departments and Agencies rely (to a degree) on rogue data sources (sometimes called black books). These are typically composed of Microsoft Excel spreadsheets compromised of copied and adjusted enterprise data, home grown Access databases, or data stored in specific analysis applications. In this module, we identify strategies for:

  • performing an audit to create a list of black books
  • understanding the forces driving their creation and ongoing maintenance
  • reducing their number and relative importance
  • migrating to more robust enterprise data sources
Product Code: DC-13
Course Duration (hours): 4
Data Mapping: Identifying and Managing Organizational Data Sources
Data Mapping: Identifying and Managing Organizational Data Sources Image

In this module, we look at tools to map the data sources that are utilized by a department, or group within a department, at a high level. This is a critical activity that allows us to set up a number of value add activities, including data management, identification of data relationships as part of data lineage analysis (where data comes from, what happens to it and where it moves over time), and discovery of hidden sensitive data and consolidation of multiple data sources.

Aimed at non technical managers, this module will enable participants to:

  • create a high level view of the sources of data that support a group within a department
  • understand the inter relationships between the data sources
  • estimate the level of risk associated with the group data management approach
  • align data requirements to group business requirements
  • visit data analysis approaches that allow a deeper understanding of their data
Product Code: DC-14
Course Duration (hours): 4
Visualizing Performance: Best Practices in Management Dashboard Design
Visualizing Performance: Best Practices in Management Dashboard Design Image

Poor data dashboard design comes from poor requirements analysis. Typically, dashboard design is left to data visualization experts; providing senior management with a list of best practices helps to build dynamic and effective dashboards from the outset. In this module, participants will learn to:

  • effectively engage with the end users to properly define the context of the dashboard
  • understand the importance of narrative and storyboarding as part of the dashboard design process
  • understand what design elements are key to engaging the end user
  • what charts to use with specific types of data and storytelling objectives
Product Code: DC-15
Course Duration (hours): 4
Management Dashboard Design Workshop
Management Dashboard Design Workshop Image

This module is designed to compliment the courses in DC-15 Visualizing Performance: Best Practices in Management Dashboard Design.

In this module we interactively walk through a dashboard requirements process including gathering end user and organization requirements, story boarding, and high level design process.

Product Code: DC-16
Course Duration (hours): 4
Identifying Key Performance indicators
Identifying Key Performance indicators Image

A Key Performance Indicator (KPI) is a performance metric that allows organizations to understand the relative “health” of a department or group by monitoring activity over time. In a data focused workplace, all KPIs need to be well defined and monitored over time. Additionally, with the advent of ever easier to use analysis tools and access to broader data, KPIs that were not available in the past are now measurable. In this module, participants will learn::

  • how to develop strategies and frameworks for KPI discovery
  • the importance of defining KPI calculations
  • identification and management of KPI data sources
  • about tools for KPI management
  • how to publish KPIs through Business Intelligence Dashboards
Product Code: DC-17
Course Duration (hours): 4
Preparing to Publish Open Data
Preparing to Publish Open Data Image

As the focus for openness and transparency grows, the requirement to push more departmental data to the GOC open data portal becomes crucial. This is a time consuming process; it becomes important for departments to set up a streamlined set of workflows and processes to ensure efficiency and data quality. In this module, participants will get an overview of:

  • best practices in publishing open data
  • how to ensure consistency in publishing open data sets over time
  • standards and protocols in publishing open data
  • quality assurance of open data
Product Code: DC-18
Course Duration (hours): 4
Collaborative Show-and-Tell
Collaborative Show-and-Tell Image

This module is a pre requisite to obtain the course certification. As part of the certification process, participants are expected to present on a topic they learned through their training and present it to a group for critique and feedback. A mini report and a presentation are required to be submitted for Data Action Lab review and records.

Product Code: DC-19
Course Duration (hours): 4
Introduction to Data Science
Workshops and courses that will get you started as a data scientist
Data Insights Fundamentals
Data Insights Fundamentals Image

Some fundamental ideas and perspectives apply to any kind of data practice. This course introduces learners to these fundamentals by providing case studies in data analysis and machine learning, presenting, in broad strokes, the underlying concepts that support data-related work and leaving them with some thought-provoking questions on these topics to ponder and discuss. The main goal of this course is to ensure that learners start their data practitioner or data scientist journey in the right direction.

Product Code: DAB-1
Course Duration (hours): 6
Data Processing
Data Processing Image

Data analysis can’t happen without data, and that data must come from somewhere. Data collection and and data processing typically take up the bulk of the time spent on any data project; how well this is accomplished carries through to the end of the project.
In this course, we survey the options for cleaning and transforming the data in order to make it more suitable for analysis.

Product Code: DAB-3
Course Duration (hours): 6
Data Engineering Basics
Data Engineering Basics Image

(details coming soon)

Product Code: DAB-4
Course Duration (hours): 6
Basic Data Analysis Techniques
Basic Data Analysis Techniques Image

This course is where the “rubber hits the road” and where learners start to work with data in a hands-on fashion. Its focus is on putting into practice, in a preliminary and basic way, many of the topics used in data analysis: data visualization, data exploration, data wrangling, and data modeling. This is done via basic analyses of data: summaries of variables, simple calculations related to these summaries, exploring subsets of the data, and gaining some basic insights into the information contained in datasets.

Product Code: DAB-5
Course Duration (hours): 6
Measures and Metrics
Measures and Metrics Image

Devising well-constructed strategies to measure the properties of key objects of interest, and then combining these measures into more abstract metrics that relate to research hypotheses or organization goals is an important component of data analysis. Measures and metrics are typically very specific to a domain or problem of interest, but case studies in one domain can provide ideas and best practices that are applicable to others. In this course, in addition to considering some of the fundamental concepts relating to these topics, learners are provided with several case studies of measures and metric development.

Product Code: DAB-6
Course Duration (hours): 6
Data and Information Architecture
Data and Information Architecture Image

Data and knowledge architecture concepts are critical in designing a data-driven project, and there have been a number of new and important developments on that front in recent years (e.g. NoSQL, graph databases, data lakes). The high-level goal of this course is to expose learners to many of the concepts and terms at play in today’s data world and to help them to decide which of these is most applicable to their particular data projects.

Product Code: DAB-7
Course Duration (hours): 6
Predictive Analytics
Predictive Analytics Image

Once the dataset has been successfully explored, described, and cleaned, analysts are in a position to use it to do more than just understand what has already happened. With enough of the right kind of data, they may also be able to predict novel or future occurrences. Predictive analysis has traditionally relied on regression as its technique of choice. New types and increasing amounts of data have led to the recent development of new techniques in this area, including time series analysis techniques and machine learning techniques, such as neural networks. This course gives an overview of these prominent prediction techniques, which provides learners with a starting point from which to begin developing predictive analysis skills.

Product Code: DAB-8
Course Duration (hours): 6
Simple Visualization Methods
Simple Visualization Methods Image

Prior to running analyses, it is crucial to gain an understanding of the dataset and how it is behaving. This process starts while cleaning the data. Increasingly sophisticated visualization strategies can play an important role at this stage, as well as at the end of the data analysis process, when insights are presented to others. This course presents simple methods to visualize data, with R/Python examples.

Product Code: DV-1
Course Duration (hours): 6
Multivariate Visualization Methods and Design Suggestions
Multivariate Visualization Methods and Design Suggestions Image

Prior to running analyses, it is crucial to gain an understanding of the dataset and how it is behaving. This process starts while cleaning the data. Increasingly sophisticated visualization strategies can play an important role at this stage, as well as at the end of the data analysis process, when insights are presented to others. This course presents mutlivariate methods to visualize data, with R/Python examples, and design suggestions to generate engaging visualizations.

Product Code: DV-2
Course Duration (hours): 6
Data Visualization
Courses related to all aspects of the visualization of data
Best Practices in Data Visualization
Best Practices in Data Visualization Image

Poorly designed visualizations (graphs, reports, charts, slides etc.) can lead to confusion and in the worst case erroneous business decisions. End users are constantly seeking the best ways to understand the data behind the data. The most effective way to help end users is by making it visual for them. This module is aimed at taking participants through the basics of data visualization and design whether you are creating Power BI interactive reports, generating charts in Excel or management presentations in PowerPoint. This module will help you to:

  • Effectively engage with the end users to properly define reporting context
  • Understand the importance of narrative and storyboarding as part of the design process
  • Understand what design elements engage inconic, short and long term memory
  • Matching visualizations to data, including best practices and implementation hacks (Excel and Power BI) for:
    • Interactive text, Data tables, Data table heatmaps, Scatterplots and bubble plots, Line charts, Bar Charts (Vertical & Horizontal), Stacked Bar Charts (Vertical & Horizontal), 100% Bar Charts (Vertical & Horizontal), Area Charts, Waterfall Charts, Treemaps, Funnel Charts, Key Performance Indicator Gauges, Data Geographical Maps and Choropleth Maps
  • Charts and visualizations to avoid
  • Fully understand the basic rules of Design and Layout including:
    • Gestalt Principles, Pre-attentive Attributes, Decluttering your charts, dashboards and reports, Size and positioning, Basic colour rules and introduction to colour wheel calculations
Product Code: DV-5
Course Duration (hours): 8
Data Visualization for Analysis
Data Visualization for Analysis Image

Data visualizations can be used for reporting endeavours in a variety of manners, but they can also be used to explore data and set the stage for more in-depth analysis, and for insight extraction. In this module, participants will

  • Learn about the different roles of data visualization in the data analysis process.
  • Increase their understanding of how to represent simultaneously multiple dimensions.
  • Learn some of the strategies and considerations used to create good post-analysis visualizations.
  • Learn the difference between a visualization and an infographic.
  • Improve their judgment about the quality of data visualizations.

In particular, participants will study the use of data visualizations for

  • Detecting anomalous and invalid entries
  • Shaping data transformations
  • Getting a sense for the data
  • Identifying hidden data structure

They will also study the fundamental principles of analytical design and learn how to recognize their application in a number of case studies, Finally, they will study the grammar of graphics.

Product Code: DV-6
Course Duration (hours): 8
Data Visualization Laboratory
Data Visualization Laboratory Image

This lab is designed for participants to cement their data visualization skills and to develop competencies. In a collaborative environment, participants can bring along their own data set or use an example data set provided by Data Action Lab. Visualizations will be created and constructively criticized by all attendees.

This lab is software tool agnostic, typically attendees create visualizations in Excel, Power BI, SAS, R, Python or any other tool of their choice.

Product Code: DV-7
Course Duration (hours): 8
Learning from the Past - Data Visualizations That Changed History
Learning from the Past - Data Visualizations That Changed History Image

From John Snows cholera map, through the Nightingale military mortality Rose Charts  to Minard’s March to Moscow, history is replete with amazing examples of data visualization that we can take lessons from and apply to our work today.

This course guides participants through a number of history changing visualizations and the group will break down the key elements of each one to come up with a list of best practices, concepts and approaches that can be applied in the environment today using new tools and techniques.

Product Code: DV-8
Course Duration (hours): 8
Practical Data Analysis
Strategies and tools for applying data analysis techniques at work
Grammar of Graphics and ggplot2
Grammar of Graphics and ggplot2 Image

The French idiomatic expression “l’habit ne fait pas le moine” cautions analysts and data consumers alike not to fall into the trap laid by pretty pictures: content is more important than style. In a world where stakeholder buy-in and data storytelling is becoming increasingly important, however, there is no denying that great content and good visuals provide a significant upgrade on great content alone. In this course, we discuss the grammar of graphics (as implemented in the R tidyverse package ggplot2).

Product Code: DV-3
Course Duration (hours): 6
A Machine Learning Capstone Project
A Machine Learning Capstone Project Image

(details to come)

Product Code: LBD-1
Course Duration (hours): 24
A Text Mining Project
A Text Mining Project Image

(details coming soon)

Product Code: LBD-2
Course Duration (hours): 24
A Data Science Pipeline
A Data Science Pipeline Image

(details coming soon)

Product Code: LBD-3
Course Duration (hours): 24
Putting it All Together
Putting it All Together Image

(details coming soon)

Product Code: LBD-4
Course Duration (hours): 24
Data Processing and Preparation
Data Processing and Preparation Image

Before data can be used for increased awareness, decision support and knowledge discovery, it must be transformed from its raw state into one that is valid, usable and applicable to a particular problem. This half-day workshop provides a first pass look at some of the many different elements of data processing: data transformation, data validation, data cleaning and dealing with missing data, as well as some of the typical considerations and issues that arise at each of these data processing stages.

Product Code: AI-2
Course Duration (hours): 3
Data and Information Architectures
Data and Information Architectures Image

Data analysis can only occur within the context of a supporting data architecture. Although the technological underpinnings and exact construction of such architectures can be vary, there are design principals that can be defined and described across technologies. This half-day workshop introduces a number of different high level data and information architectures, including databases, data lakes, ontogies, NoSQL and graph databases. Within the context of these architectures, the module also discusses, more generally what it means to structure data, and why choosing the correct data structure is essential in enabling the intended use of your data.

Product Code: AI-3
Course Duration (hours): 3
Becoming A Data Translator
Becoming A Data Translator Image

Hot on the heels of the data science explosion, data translators are becoming the next big in-demand role in data-driven projects. But what is a data translator, and what do you need to know to become one? This one-day workshop will introduce you to the data translator role, which focuses on helping data scientists and business stakeholders communicate with each other. The workshop will also review the fundamental concepts and areas of expertise with which all data translators must be familiar, including: data science, data engineering, business intelligence and data management. The workshop will conclude by reviewing the typical parts and processes of data science projects, and explore the role of the data translator at each stage.

Product Code: AI-4
Course Duration (hours): 6
Programming BootCamp: From Novice to Next Steps
Programming BootCamp: From Novice to Next Steps Image

This two-week bootcamp will take you from not knowing anything about computer programming (a ‘Noob’ in the programming world) to starting to self-learn with confidence. The first week will focus on an overview of programming practices and strategies, along with a discussion of other computer concepts relevant to programming: types of programming languages and programmers, programming best practices, programming theory and practice, operating systems and file systems, internet and cloud protocols. There will be hands-on exercises in the first week, but they will not require participants to write code from scratch. The second week will be a series of labs where participants learn to write a series of simple programs using both Python (as an example of a general programming language) and R (as an example of a specialty programming language, focusing on data manipulation, analysis and visualization), culminating in a cap-stone simple web-app project.

Product Code: AI-6
Course Duration (hours): 40
Machine Learning and AI Basics
How to carry out machine learning and basic AI techniques
Statistical Learning and Association Rules
Statistical Learning and Association Rules Image

After having spent some time on data preparation, data cleaning, data exploration, and on a survey of the basics of programming, as well as on mathematical and statistical preliminaries, learners are now ready to discuss the general tasks and problems of Statistical Learning (also called Machine Learning). In this course, learners are additionally introduced to their first (unsupervised) learning task: association rules mining.

Product Code: ML-1
Course Duration (hours): 6
Introduction to Clustering
Introduction to Clustering Image

When it comes to using mathematical and statistical language and formalism, supervised learning slots into a role akin to that played by physics: complex, yes, but quite well-suited to the language and with a long history of applications. Unsupervised learning (such as clustering) is more similar to biology: it has not been studied with the same formalism and to the same extent, because it is, quite simply, harder to do so (not in the sense that the algorithms are too complicated, but in the sense that their results are harder to validate). Interest in those methods is increasing, however. In this MCT, we discuss the basics of clustering and tackle some of its issues and challenges. We also introduce k-Means, hierarchical clustering, and discuss clustering validation.

Product Code: ML-2
Course Duration (hours): 9
Spotlight on Clustering I
Spotlight on Clustering I Image

In this course, we introduce a number of clustering methods: DBSCAN, spectral clustering, and ensemble clustering.

Product Code: UL-1
Course Duration (hours): 9
Spotlight on Clustering II
Spotlight on Clustering II Image

In this course, we introduce a number of clustering methods: EM clustering, latent Dirichlet allocation, and fuzzy clustering.

Product Code: UL-2
Course Duration (hours): 9
Introduction to Classification
Introduction to Classification Image

Supervised learning tends to be easier to set-up than unsupervised learning, given the general clarity of the questions that are tackled and the ease with which we can evaluate a model’s performance. In some sense, classification and value estimation (regression) are the quintessential machine learning tasks; more so than unsupervised learning methods. In this course, we discuss the basics of classification, and some its issues and challenges. We also introduce decision trees, naïve Bayes classifiers, and discuss performance evaluation.

Product Code: ML-3
Course Duration (hours): 9
Spotlight on Classification and Value Estimation I
Spotlight on Classification and Value Estimation I Image

In this course, we introduce a number of classification and value estimation methods: logistic regression, regression trees, support vector machines, and MARS.

Product Code: SL-1
Course Duration (hours): 9
Spotlight on Classification and Value Estimation II
Spotlight on Classification and Value Estimation II Image

In this course, we introduce a number of classification and value estimation methods: rare occurrence models, bagging and random forests, and boosting methods.

Product Code: SL-2
Course Duration (hours): 9
Text Mining I - Text Processing
Text Mining I - Text Processing Image

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss the intricacies of preparing text data for analysis.

Product Code: TM-1
Course Duration (hours): 6
Text Mining II - Sentiment Analysis
Text Mining II - Sentiment Analysis Image

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss text classification and sentiment analysis.

Product Code: TM-2
Course Duration (hours): 6
Text Mining III - Text Visualization and Misc.
Text Mining III - Text Visualization and Misc. Image

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss the myriads way text data can be visualized.

Product Code: TM-3
Course Duration (hours): 6
Natural Language Processing I - NLP Basics
Natural Language Processing I - NLP Basics Image

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss the basics of natural language processing.

Product Code: NLP-1
Course Duration (hours): 6
Natural Language Processing II - NLP Tasks
Natural Language Processing II - NLP Tasks Image

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss other applications of natural language processing: named-entity recognition, semantic parsing, summarization, etc.

Product Code: NLP-2
Course Duration (hours): 6
Natural Language Processing III - Topic Modeling
Natural Language Processing III - Topic Modeling Image

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss topic modeling.

Product Code: NLP-3
Course Duration (hours): 6
Math/Stats for Machine Learning and AI
Math/Stats for Machine Learning and AI Image

To be comfortable with machine learning, learners need some knowledge of a number of mathematical disciplines, including statistics, linear algebra, multi-variable calculus, and mathematical modelling. This course provides learners with a high-level survey of some of the fundamental concepts of these disciplines, focusing on a few key topics in each. The goal of the course is to orient the learner towards these disciplines and concepts, to allow for future in-depth learning.

Product Code: DAB-9
Course Duration (hours): 12
AI/ML: Introduction to Techniques and Processes
AI/ML: Introduction to Techniques and Processes Image

This half-day workshop provides participants with an introduction to:

  • The foundational components of AI and ML.
  • Business functions (processes, etc.) typically involved in AI/ML projects.
  • Hardware and software requirements and resources needed for AI/ML projects (staff, equipment, expertise), including some discussion of API supporting technologies and data.

Where possible, relevant government examples will be used to illustrate these topics, and during the workshop there will be additional discussion with workshop attendees about where AI could usefully be applied in their work contexts.

Product Code: AI-1
Course Duration (hours): 3
Microsoft Power BI
Courses to teach the use and application of Microsoft Power BI.
An overview of Microsoft Power BI
An overview of Microsoft Power BI Image

This module is designed for the absolute Power BI beginner. We walk the participants through the Power BI basics including:

  • How Power BI fits into a larger software framework
  • Where, and where not to use Power BI
  • Excel vs Power BI – pros and cons
  • A Power BI walkthrough
  • Power Query (with a brief overview of M)
  • Data Modeling view
  • Data layout view
  • Data visualization view
  • What is DAX and how it is used
  • How to publish with Power BI

At the end of this session participants should be comfortable with what Power BI should be used for and have the ability to open a simple data set and create some simple visualizations

Product Code: PBI-1
Course Duration (hours): 4
Power BI - Building Basic Visualizations
Power BI - Building Basic Visualizations Image

This module is aimed at taking participants through the initial stages of inputting data and creating their first interactive charts, reports and visualizations. This module will help you to:

  • Understand the importance of clean data
  • How to import data from single and multiple data sources
  • Manipulating the data as it is imported into Power BI
  • Creating our first calculations
  • Creating our first custom columns
  • Creating our first charts
  • Basic interactive filtering
  • Creating basic hierarchies of data
  • How to layout a report and dashboard
  • How to publish reports and dashboards to end users
Product Code: PBI-2
Course Duration (hours): 8
Power BI - Beyond the Basics
Power BI - Beyond the Basics Image

This module is aimed at taking participants past their first chart creation in Power BI and to shortcut the user to some relatively sophisticated visualizations that are not technically difficult to create. The module will help you to:

  • Get a head start on Data Modeling
  • Get up to speed in DAX – effective and easy top tips
  • Get up to speed in M – effective and easy top tips
  • How to overcome common data analysis issues
  • Useful intermediate Power BI “hacks”
  • Introduction to non-standard charts
Product Code: PBI-3
Course Duration (hours): 8
Power BI - A Deeper Dive into Data Modeling
Power BI - A Deeper Dive into Data Modeling Image

This module is designed to look in more depth in data modeling in Power BI. Excel users are very used to data presented as a flat file (a tab or table) but to extract the greatest value from Power BI we need to look at our data from a dynamic, relational perspective. In this course we will:

  • Learn in detail what makes a good data model
  • Understand how to optimize data models for data visualization
  • Where to use cross reference tables
  • How to create dynamic cross reference tables that adjust to changing input data
  • How to optimize data models for large data sets
Product Code: PBI-4
Course Duration (hours): 4
Power BI - Integrating R and Python
Power BI - Integrating R and Python Image

In this module we will work with participants to integrate both R and Python script into Power BI. A high-level understanding of either R or Python is required but the course presenter will walk participants through some basic R script and/or Python. If this course is purchased as an in-house module we can concentrate specifically on R or Python or both at the discretion of the client. In this course participants will learn how to:

  • Embed R script to import data in Power BI
  • Embed Python to import data in Power BI
  • Combining imported data into existing Power BI data model
  • Using R script and/or Python to create interactive visuals in Power BI
Product Code: PB-5
Course Duration (hours): 4
Power BI - Supervised Self Learning
Power BI - Supervised Self Learning Image

There are many online resources to learn Power BI (for example the Microsoft / EDX course). Unfortunately, GOC employees are not always able to access these courses at their desk or at home.

To address this issues Data Action Lab hosts interactive learning environment where participants can work through the on-line learning in a supervised environment. The learning is self paced and a technical expert is on hand to help the learner through any issues. This module can be delivered in house but there is a minimum commitment of three months once per week

Product Code: PBI-6
Course Duration (hours): 32
Power BI - Monthly Laboratory
Power BI - Monthly Laboratory Image

The Data Actional Lab holds a series of Data Labs on various topics. The Data Lab on the third week of each month is dedicated to GOC Power BI users. Each month is different but typically participants bring along problems for the group to solve. To attend the ongoing Data Labs a monthly attendance fee is required. The payment of this fee allows the organization to send up to five participants to any of the labs through the month. For more details please see the Data Action Lab website

Product Code: PBI-7
Course Duration (hours): 48
AI/ML Toolbox
Technique and tool focused workshops for data analysts and data scientists
Programming Basics
Programming Basics Image

Programming languages go in and out of style. To be a strong programmer, it’s important to understand not just the ins and outs of a particular programming language, but how computer languages and computing infrastructure work more generally. In this course, learners are introduced to some of the core concepts of computer programming, in a language-agnostic way.

Product Code: DAB-2
Course Duration (hours): 6
Introduction to Dashboards
Introduction to Dashboards Image

The French idiomatic expression “l’habit ne fait pas le moine” cautions analysts and data consumers alike not to fall into the trap laid by pretty pictures: content is more important than style. In a world where stakeholder buy-in and data storytelling is becoming increasingly important, however, there is no denying that great content and good visuals provide a significant upgrade on great content alone. In this course, we introduce dashboards and data storytelling.

Product Code: DV-4
Course Duration (hours): 6
Reporting and Deployment
Reporting and Deployment Image
Product Code: ST-9
Course Duration (hours): 12
Web Scraping and Automated Data Collection
Web Scraping and Automated Data Collection Image

Data analysis can’t happen without data, and that data must come from somewhere. Data collection and and data processing typically take up the bulk of the time spent on any data project; how well this is accomplished carries through to the end of the project. In this course, we consider the main elements required to succeed in data collection, as well as the many ways this activity can go awry.

Product Code: ST-3
Course Duration (hours): 18
Data Science With Streams
Data Science With Streams Image
Product Code: ST-4
Course Duration (hours): 12
R for Data Science
R for Data Science Image

This full-day in-person, hands-on workshop provides participants with information on using R for Data Science. It is intended for people who already have a programming background. The workshop is structured as follows:

Morning – Theory:
Review of R as a programming language:
History and comparison with other languages (e.g. Python)
Programming environment options – R Studio, R Markdown
Overview of key packages: Statistical Packages, Machine Learning Packages, TidyVerse (data processing + visualization), Shiny
Programming basics – conceptual overview
Brief Review of Relevant Statistical Concepts:
Descriptive Statistics
Statistical Modelling
Comparison between Statistics and Machine Learning

Afternoon – Hands-On:
Quick hands-on walk through of R command-line and R-Studio (e.g. running scripts, installing packages)
Getting into R program – with Pre-Worked Examples in R-Markdown
Practice Exercises and Lab Time

Product Code: AI-5
Course Duration (hours): 6
Advanced Topics
Specialized topics in data science for those who already have the fundamentals
A Big Data Adventure
A Big Data Adventure Image

Data science tasks break down when the datasets become too large. Throw enough time and money at this specific problem and it will eventually evaporate. But what can one achieve on a budget? In this course, participants will learn to tackle simple Big Data problems using Spark and H20.

Product Code: ST-1
Course Duration (hours): 12
Feature Selection and Dimension Reduction
Feature Selection and Dimension Reduction Image

Data mining is the collection of processes by which we can extract useful insights from data. Inherent in this definition is the idea of data reduction: useful insights (whether in the form of summaries, sentiment analyses, etc.) ought to be “smaller” and “more organized” than the original raw data. The challenges presented by high data dimensionality (the so-called curse of dimensionality) must be addressed in order to achieve insightful and interpretable analytical results. In this course, we introduce the basic principles of dimensionality reduction and a number of feature selection methods (filter, wrapper, regularization), discuss some advanced topics (SVD, spectral feature selection, UMAP and other topological reduction methods), with examples.

Product Code: ST-10
Course Duration (hours): 12
Introduction to Deep Learning and Reinforcement Learning
Introduction to Deep Learning and Reinforcement Learning Image

(details coming soon)

Product Code: ST-2
Course Duration (hours): 18
Recommender Systems
Recommender Systems Image

(details coming soon)

Product Code: ST-5
Course Duration (hours): 12
Bayesian Data Analysis
Bayesian Data Analysis Image

Bayesian analysis is sometimes maligned by data analysts, due in part to the perceived element of arbitrariness associated with the selection of a meaningful prior distribution for a specific problem and the (former) difficulties involved with producing posterior distributions for all but the simplest situations. On the other hand, we have heard it said that “while classical data analysts need a large bag of clever tricks to unleash on their data, Bayesians only ever really need one.” With the advent of efficient numerical samplers, modern data analysts cannot shy away from adding the Bayesian arrow to their quiver. In this course, we will introduce the basic concepts underpinning Bayesian analysis, and present a small number of examples that illustrate the strengths of the approach.

Product Code: ST-6
Course Duration (hours): 12
Anomaly Detection
Anomaly Detection Image

With the advent of automatic data collection, it is now possible to store and process large troves of data. There are technical issues associated to massive data sets, such as the speed and efficiency of analytical methods, but there are also problems related to the detection of anomalous observations and the analysis of outliers. Extreme and irregular values behave very differently from the majority of observations. For instance, they can represent criminal attacks, fraud attempts, targeted attacks, or data collection errors. As a result, anomaly detection and outlier analysis play a crucial role in cybersecurity, quality control, etc. The (potentially) heavy human price and technical consequences related to the presence of such observations go a long way towards explaining why the topic has attracted attention in recent years. In this course, we will review various detection methods, and provide a comparative analysis of algorithms (performance, limitations), illustrated with the help of some practical examples, and with particular attention paid to supervised and unsupervised methods.

Product Code: ST-7
Course Duration (hours): 12
Analysis of (Social) Network Data
Analysis of (Social) Network Data Image

(details coming soon)

Product Code: ST-8
Course Duration (hours): 12
Data Strategy and Governance
List of courses that address Data Strategy and Governance with a focus on GOC Digital Strategy.
Developing a Data Strategy Roadmap Image
Developing a Data Strategy Roadmap
In the recent Privy Council report “A Data Strategy Roadmap for the Federal Public Service”, a roadmap was laid out for GOC Departments to create Data Strategy and Governance frameworks and to implement them through a robust Data Str... Read More
Product Code: DC-1
Course Duration (hours): 4
Developing a Data Governance Strategy Image
Developing a Data Governance Strategy
This module aids participants with the practical implementation of a Data Governance Strategy. All GOC Departments are now, at a high level, developing Data Strategies to align with the Privy Council report “A Data Strategy Road... Read More
Product Code: DC-2
Course Duration (hours): 4
Data Strategy and Governance Checklist Review Image
Data Strategy and Governance Checklist Review
This module uses the information provided in DC 1 Developing a Data Strategy Roadmap and DC 2 Developing a Data Governance Strategy and walks participants through a pre defined checklist to assess where their Department, Group or Line of... Read More
Product Code: DC-3
Course Duration (hours): 4
Empowering a Data Focused Workplace Image
Empowering a Data Focused Workplace
This module provides tips and approaches to help empower a data focused workplace. It is not sufficient to rely on a small number of individuals to manage and use data – all employees need to understand their role in the creation, anal... Read More
Product Code: DC-4
Course Duration (hours): 4
Analyzing Data to Identify Improvement Activities Image
Analyzing Data to Identify Improvement Activities
This module investigates methods to link the results of data analysis with departmental or group objectives. The standard is often “analysis for the sake of analysis”. In this module, we show how to build an analysis framework th... Read More
Product Code: DC-5
Course Duration (hours): 4
Initiating and Managing AI/ML Projects I Image
Initiating and Managing AI/ML Projects I
This is the first of three modules on running Artificial intelligence (AI) and Machine Learning (ML) projects. Compared to regular projects, these project categories typically require a different approach to set up and run. Due to the si... Read More
Product Code: DC-6
Course Duration (hours): 4
Initiating and Managing AI/ML Projects II Image
Initiating and Managing AI/ML Projects II
This is the second of three modules on running Artificial intelligence (AI) and Machine Learning (ML) projects. in this module, you will learn: how to understand AI/ML infrastructure requirements AI/ML techniques tr... Read More
Product Code: DC-7
Course Duration (hours): 4
AI/ML Projects: Case Study Workshop Image
AI/ML Projects: Case Study Workshop
The third and final module in our Artificial intelligence (AI) and Machine Learning (ML) project series. in this module, participants are presented with a series of case studies which are analyzed to derive lessons learned and best pract... Read More
Product Code: DC-8
Course Duration (hours): 4
Data Roles: Who to Hire in the information Workplace Image
Data Roles: Who to Hire in the information Workplace
In a dynamically changing workplace, it is difficult to understand what new and changing roles are required to build a data focused workplace. in this module, we outline some of the key new roles that may be required and what competencie... Read More
Product Code: DC-9
Course Duration (hours): 4
Data Toolbox Overview I (self service tools) Image
Data Toolbox Overview I (self service tools)
The first of two modules providing an overview of standard software tools. This module looks at self service tools including (other tools may be included at the discretion of Data Action Lab or by request): Code based analys... Read More
Product Code: DC-10
Course Duration (hours): 4
Data Toolbox Overview II (enterprise tools) Image
Data Toolbox Overview II (enterprise tools)
The second of two modules providing an overview of standard software tools. This module looks at enterprise tools, including tools provided by (other tools may be included at the discretion of Data Action Lab or by request): ... Read More
Product Code: DC-11
Course Duration (hours): 4
A Manager’s Guide to Data Engineering Image
A Manager’s Guide to Data Engineering
A department’s data analyses are only as good as the data that they access. Essentially, data engineering is the creation of data pipelines that enable the data scientists and analysts to do their work properly. As the workplace become... Read More
Product Code: DC-12
Course Duration (hours): 4
Black Books: Identifying and Managing Rogue Data Sources Image
Black Books: Identifying and Managing Rogue Data Sources
All groups within GOC Departments and Agencies rely (to a degree) on rogue data sources (sometimes called black books). These are typically composed of Microsoft Excel spreadsheets compromised of copied and adjusted enterprise data, home... Read More
Product Code: DC-13
Course Duration (hours): 4
Data Mapping: Identifying and Managing Organizational Data Sources Image
Data Mapping: Identifying and Managing Organizational Data Sources
In this module, we look at tools to map the data sources that are utilized by a department, or group within a department, at a high level. This is a critical activity that allows us to set up a number of value add activities, including d... Read More
Product Code: DC-14
Course Duration (hours): 4
Visualizing Performance: Best Practices in Management Dashboard Design Image
Visualizing Performance: Best Practices in Management Dashboard Design
Poor data dashboard design comes from poor requirements analysis. Typically, dashboard design is left to data visualization experts; providing senior management with a list of best practices helps to build dynamic and effective dashboard... Read More
Product Code: DC-15
Course Duration (hours): 4
Management Dashboard Design Workshop Image
Management Dashboard Design Workshop
This module is designed to compliment the courses in DC-15 Visualizing Performance: Best Practices in Management Dashboard Design. In this module we interactively walk through a dashboard requirements process including gathering e... Read More
Product Code: DC-16
Course Duration (hours): 4
Identifying Key Performance indicators Image
Identifying Key Performance indicators
A Key Performance Indicator (KPI) is a performance metric that allows organizations to understand the relative “health” of a department or group by monitoring activity over time. In a data focused workplace, all KPIs need to be well ... Read More
Product Code: DC-17
Course Duration (hours): 4
Preparing to Publish Open Data Image
Preparing to Publish Open Data
As the focus for openness and transparency grows, the requirement to push more departmental data to the GOC open data portal becomes crucial. This is a time consuming process; it becomes important for departments to set up a streamlined ... Read More
Product Code: DC-18
Course Duration (hours): 4
Collaborative Show-and-Tell Image
Collaborative Show-and-Tell
This module is a pre requisite to obtain the course certification. As part of the certification process, participants are expected to present on a topic they learned through their training and present it to a group for critique and feedb... Read More
Product Code: DC-19
Course Duration (hours): 4
Introduction to Data Science
Workshops and courses that will get you started as a data scientist
Data Insights Fundamentals Image
Data Insights Fundamentals
Some fundamental ideas and perspectives apply to any kind of data practice. This course introduces learners to these fundamentals by providing case studies in data analysis and machine learning, presenting, in broad strokes, the underlyi... Read More
Product Code: DAB-1
Course Duration (hours): 6
Data Processing Image
Data Processing
Data analysis can’t happen without data, and that data must come from somewhere. Data collection and and data processing typically take up the bulk of the time spent on any data project; how well this is accomplished carries throug... Read More
Product Code: DAB-3
Course Duration (hours): 6
Data Engineering Basics Image
Data Engineering Basics
(details coming soon)
Product Code: DAB-4
Course Duration (hours): 6
Basic Data Analysis Techniques Image
Basic Data Analysis Techniques
This course is where the “rubber hits the road” and where learners start to work with data in a hands-on fashion. Its focus is on putting into practice, in a preliminary and basic way, many of the topics used in data analysi... Read More
Product Code: DAB-5
Course Duration (hours): 6
Measures and Metrics Image
Measures and Metrics
Devising well-constructed strategies to measure the properties of key objects of interest, and then combining these measures into more abstract metrics that relate to research hypotheses or organization goals is an important component of... Read More
Product Code: DAB-6
Course Duration (hours): 6
Data and Information Architecture Image
Data and Information Architecture
Data and knowledge architecture concepts are critical in designing a data-driven project, and there have been a number of new and important developments on that front in recent years (e.g. NoSQL, graph databases, data lakes). The high-le... Read More
Product Code: DAB-7
Course Duration (hours): 6
Predictive Analytics Image
Predictive Analytics
Once the dataset has been successfully explored, described, and cleaned, analysts are in a position to use it to do more than just understand what has already happened. With enough of the right kind of data, they may also be able to pred... Read More
Product Code: DAB-8
Course Duration (hours): 6
Simple Visualization Methods Image
Simple Visualization Methods
Prior to running analyses, it is crucial to gain an understanding of the dataset and how it is behaving. This process starts while cleaning the data. Increasingly sophisticated visualization strategies can play an important role at this ... Read More
Product Code: DV-1
Course Duration (hours): 6
Multivariate Visualization Methods and Design Suggestions Image
Multivariate Visualization Methods and Design Suggestions
Prior to running analyses, it is crucial to gain an understanding of the dataset and how it is behaving. This process starts while cleaning the data. Increasingly sophisticated visualization strategies can play an important role at this ... Read More
Product Code: DV-2
Course Duration (hours): 6
Data Visualization
Courses related to all aspects of the visualization of data
Best Practices in Data Visualization Image
Best Practices in Data Visualization
Poorly designed visualizations (graphs, reports, charts, slides etc.) can lead to confusion and in the worst case erroneous business decisions. End users are constantly seeking the best ways to understand the data behind the data. The mo... Read More
Product Code: DV-5
Course Duration (hours): 8
Data Visualization for Analysis Image
Data Visualization for Analysis
Data visualizations can be used for reporting endeavours in a variety of manners, but they can also be used to explore data and set the stage for more in-depth analysis, and for insight extraction. In this module, participants will ... Read More
Product Code: DV-6
Course Duration (hours): 8
Data Visualization Laboratory Image
Data Visualization Laboratory
This lab is designed for participants to cement their data visualization skills and to develop competencies. In a collaborative environment, participants can bring along their own data set or use an example data set provided by Data Acti... Read More
Product Code: DV-7
Course Duration (hours): 8
Learning from the Past - Data Visualizations That Changed History Image
Learning from the Past - Data Visualizations That Changed History
From John Snows cholera map, through the Nightingale military mortality Rose Charts  to Minard’s March to Moscow, history is replete with amazing examples of data visualization that we can take lessons from and apply to our work today... Read More
Product Code: DV-8
Course Duration (hours): 8
Practical Data Analysis
Strategies and tools for applying data analysis techniques at work
Grammar of Graphics and ggplot2 Image
Grammar of Graphics and ggplot2
The French idiomatic expression “l’habit ne fait pas le moine” cautions analysts and data consumers alike not to fall into the trap laid by pretty pictures: content is more important than style. In a world where stakeholder... Read More
Product Code: DV-3
Course Duration (hours): 6
A Machine Learning Capstone Project Image
A Machine Learning Capstone Project
(details to come)
Product Code: LBD-1
Course Duration (hours): 24
A Text Mining Project Image
A Text Mining Project
(details coming soon)
Product Code: LBD-2
Course Duration (hours): 24
A Data Science Pipeline Image
A Data Science Pipeline
(details coming soon)
Product Code: LBD-3
Course Duration (hours): 24
Putting it All Together Image
Putting it All Together
(details coming soon)
Product Code: LBD-4
Course Duration (hours): 24
Data Processing and Preparation Image
Data Processing and Preparation
Before data can be used for increased awareness, decision support and knowledge discovery, it must be transformed from its raw state into one that is valid, usable and applicable to a particular problem. This half-day workshop provides a... Read More
Product Code: AI-2
Course Duration (hours): 3
Data and Information Architectures Image
Data and Information Architectures
Data analysis can only occur within the context of a supporting data architecture. Although the technological underpinnings and exact construction of such architectures can be vary, there are design principals that can be defined and des... Read More
Product Code: AI-3
Course Duration (hours): 3
Becoming A Data Translator Image
Becoming A Data Translator
Hot on the heels of the data science explosion, data translators are becoming the next big in-demand role in data-driven projects. But what is a data translator, and what do you need to know to become one? This one-day workshop will intr... Read More
Product Code: AI-4
Course Duration (hours): 6
Programming BootCamp: From Novice to Next Steps Image
Programming BootCamp: From Novice to Next Steps
This two-week bootcamp will take you from not knowing anything about computer programming (a ‘Noob’ in the programming world) to starting to self-learn with confidence. The first week will focus on an overview of programming ... Read More
Product Code: AI-6
Course Duration (hours): 40
Machine Learning and AI Basics
How to carry out machine learning and basic AI techniques
Statistical Learning and Association Rules Image
Statistical Learning and Association Rules
After having spent some time on data preparation, data cleaning, data exploration, and on a survey of the basics of programming, as well as on mathematical and statistical preliminaries, learners are now ready to discuss the general task... Read More
Product Code: ML-1
Course Duration (hours): 6
Introduction to Clustering Image
Introduction to Clustering
When it comes to using mathematical and statistical language and formalism, supervised learning slots into a role akin to that played by physics: complex, yes, but quite well-suited to the language and with a long history of applications... Read More
Product Code: ML-2
Course Duration (hours): 9
Spotlight on Clustering I Image
Spotlight on Clustering I
In this course, we introduce a number of clustering methods: DBSCAN, spectral clustering, and ensemble clustering.
Product Code: UL-1
Course Duration (hours): 9
Spotlight on Clustering II Image
Spotlight on Clustering II
In this course, we introduce a number of clustering methods: EM clustering, latent Dirichlet allocation, and fuzzy clustering.
Product Code: UL-2
Course Duration (hours): 9
Introduction to Classification Image
Introduction to Classification
Supervised learning tends to be easier to set-up than unsupervised learning, given the general clarity of the questions that are tackled and the ease with which we can evaluate a model’s performance. In some sense, classification a... Read More
Product Code: ML-3
Course Duration (hours): 9
Spotlight on Classification and Value Estimation I Image
Spotlight on Classification and Value Estimation I
In this course, we introduce a number of classification and value estimation methods: logistic regression, regression trees, support vector machines, and MARS.
Product Code: SL-1
Course Duration (hours): 9
Spotlight on Classification and Value Estimation II Image
Spotlight on Classification and Value Estimation II
In this course, we introduce a number of classification and value estimation methods: rare occurrence models, bagging and random forests, and boosting methods.
Product Code: SL-2
Course Duration (hours): 9
Text Mining I - Text Processing Image
Text Mining I - Text Processing
The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into ... Read More
Product Code: TM-1
Course Duration (hours): 6
Text Mining II - Sentiment Analysis Image
Text Mining II - Sentiment Analysis
The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into ... Read More
Product Code: TM-2
Course Duration (hours): 6
Text Mining III - Text Visualization and Misc. Image
Text Mining III - Text Visualization and Misc.
The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into ... Read More
Product Code: TM-3
Course Duration (hours): 6
Natural Language Processing I - NLP Basics Image
Natural Language Processing I - NLP Basics
The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into ... Read More
Product Code: NLP-1
Course Duration (hours): 6
Natural Language Processing II - NLP Tasks Image
Natural Language Processing II - NLP Tasks
The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into ... Read More
Product Code: NLP-2
Course Duration (hours): 6
Natural Language Processing III - Topic Modeling Image
Natural Language Processing III - Topic Modeling
The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into ... Read More
Product Code: NLP-3
Course Duration (hours): 6
Math/Stats for Machine Learning and AI Image
Math/Stats for Machine Learning and AI
To be comfortable with machine learning, learners need some knowledge of a number of mathematical disciplines, including statistics, linear algebra, multi-variable calculus, and mathematical modelling. This course provides learners with... Read More
Product Code: DAB-9
Course Duration (hours): 12
AI/ML: Introduction to Techniques and Processes Image
AI/ML: Introduction to Techniques and Processes
This half-day workshop provides participants with an introduction to: The foundational components of AI and ML. Business functions (processes, etc.) typically involved in AI/ML projects. Hardware and softwa... Read More
Product Code: AI-1
Course Duration (hours): 3
Microsoft Power BI
Courses to teach the use and application of Microsoft Power BI.
An overview of Microsoft Power BI Image
An overview of Microsoft Power BI
This module is designed for the absolute Power BI beginner. We walk the participants through the Power BI basics including: How Power BI fits into a larger software framework Where, and where not to use Power BI... Read More
Product Code: PBI-1
Course Duration (hours): 4
Power BI - Building Basic Visualizations Image
Power BI - Building Basic Visualizations
This module is aimed at taking participants through the initial stages of inputting data and creating their first interactive charts, reports and visualizations. This module will help you to: Understand the importance of cle... Read More
Product Code: PBI-2
Course Duration (hours): 8
Power BI - Beyond the Basics Image
Power BI - Beyond the Basics
This module is aimed at taking participants past their first chart creation in Power BI and to shortcut the user to some relatively sophisticated visualizations that are not technically difficult to create. The module will help you to:... Read More
Product Code: PBI-3
Course Duration (hours): 8
Power BI - A Deeper Dive into Data Modeling Image
Power BI - A Deeper Dive into Data Modeling
This module is designed to look in more depth in data modeling in Power BI. Excel users are very used to data presented as a flat file (a tab or table) but to extract the greatest value from Power BI we need to look at our data from a dy... Read More
Product Code: PBI-4
Course Duration (hours): 4
Power BI - Integrating R and Python Image
Power BI - Integrating R and Python
In this module we will work with participants to integrate both R and Python script into Power BI. A high-level understanding of either R or Python is required but the course presenter will walk participants through some basic R script a... Read More
Product Code: PB-5
Course Duration (hours): 4
Power BI - Supervised Self Learning Image
Power BI - Supervised Self Learning
There are many online resources to learn Power BI (for example the Microsoft / EDX course). Unfortunately, GOC employees are not always able to access these courses at their desk or at home. To address this issues Data Action Lab ... Read More
Product Code: PBI-6
Course Duration (hours): 32
Power BI - Monthly Laboratory Image
Power BI - Monthly Laboratory
The Data Actional Lab holds a series of Data Labs on various topics. The Data Lab on the third week of each month is dedicated to GOC Power BI users. Each month is different but typically participants bring along problems for the group t... Read More
Product Code: PBI-7
Course Duration (hours): 48
AI/ML Toolbox
Technique and tool focused workshops for data analysts and data scientists
Programming Basics Image
Programming Basics
Programming languages go in and out of style. To be a strong programmer, it’s important to understand not just the ins and outs of a particular programming language, but how computer languages and computing infrastructure work more gen... Read More
Product Code: DAB-2
Course Duration (hours): 6
Introduction to Dashboards Image
Introduction to Dashboards
The French idiomatic expression “l’habit ne fait pas le moine” cautions analysts and data consumers alike not to fall into the trap laid by pretty pictures: content is more important than style. In a world where stakeholder... Read More
Product Code: DV-4
Course Duration (hours): 6
Reporting and Deployment Image
Reporting and Deployment
Product Code: ST-9
Course Duration (hours): 12
Web Scraping and Automated Data Collection Image
Web Scraping and Automated Data Collection
Data analysis can’t happen without data, and that data must come from somewhere. Data collection and and data processing typically take up the bulk of the time spent on any data project; how well this is accomplished carries throug... Read More
Product Code: ST-3
Course Duration (hours): 18
Data Science With Streams Image
Data Science With Streams
Product Code: ST-4
Course Duration (hours): 12
R for Data Science Image
R for Data Science
This full-day in-person, hands-on workshop provides participants with information on using R for Data Science. It is intended for people who already have a programming background. The workshop is structured as follows: Morning –... Read More
Product Code: AI-5
Course Duration (hours): 6
Advanced Topics
Specialized topics in data science for those who already have the fundamentals
A Big Data Adventure Image
A Big Data Adventure
Data science tasks break down when the datasets become too large. Throw enough time and money at this specific problem and it will eventually evaporate. But what can one achieve on a budget? In this course, participants will learn to tac... Read More
Product Code: ST-1
Course Duration (hours): 12
Feature Selection and Dimension Reduction Image
Feature Selection and Dimension Reduction
Data mining is the collection of processes by which we can extract useful insights from data. Inherent in this definition is the idea of data reduction: useful insights (whether in the form of summaries, sentiment analyses, etc.) ought t... Read More
Product Code: ST-10
Course Duration (hours): 12
Introduction to Deep Learning and Reinforcement Learning Image
Introduction to Deep Learning and Reinforcement Learning
(details coming soon)
Product Code: ST-2
Course Duration (hours): 18
Recommender Systems Image
Recommender Systems
(details coming soon)
Product Code: ST-5
Course Duration (hours): 12
Bayesian Data Analysis Image
Bayesian Data Analysis
Bayesian analysis is sometimes maligned by data analysts, due in part to the perceived element of arbitrariness associated with the selection of a meaningful prior distribution for a specific problem and the (former) difficulties involve... Read More
Product Code: ST-6
Course Duration (hours): 12
Anomaly Detection Image
Anomaly Detection
With the advent of automatic data collection, it is now possible to store and process large troves of data. There are technical issues associated to massive data sets, such as the speed and efficiency of analytical methods, but there are... Read More
Product Code: ST-7
Course Duration (hours): 12
Analysis of (Social) Network Data Image
Analysis of (Social) Network Data
(details coming soon)
Product Code: ST-8
Course Duration (hours): 12