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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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
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