Certificat de perfectionnement professionnel en science des données et apprentissage automatique

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Les programmes en sciences des données, de plus en plus en demande et maintenant plus accessibles

D’ingénieur en logiciels à ingénieur en données grâce au certificat en science des données et apprentissage automatique de l’Université McGill

La science des données : de plus en plus accessible

Cursus

Cours obligatoires
YCBS 255 Statistical Machine Learning (8 CEUs)
Fundamental statistical machine learning concepts and tools using Python. Emphasis on descriptive statistics, statistical distributions, random number generation, basic data visualization; linear regression; basic classification; error estimation: cross-validation, bias-variance trade-off; shrinkage methods; dimension reduction; beyond linearity: smoothing splines, local regression, additive models; tree and ensemble methods; powerful classifiers; unsupervised learning.



(30 INFORMS PDUs)

The PDUs earned through this non-credit-bearing course can be used by CAP and aCAP certificants to satisfy the 30 PDUs needed to renew their certification every three (3) years. More info.
YCBS 256 Data Science for Business Decisions (8 CEUs)
Overview of how data science can help drive business decisions and create new business models. Emphasis on data strategy, the data science lifecycle and process, business and analytics problem framing, overcoming challenges of implementing a data-driven business, including ethics, data governance, and privacy. Application of data science across various industries and business areas. Data science tools, including Alteryx and Tableau for data preparation, analysis, and visualization.


This course is aligned with the IIBA’s Certification in Business Data Analytics (IIBA®-CBDA) competencies. More information.




(30 INFORMS PDUs)

The PDUs earned through this non-credit-bearing course can be used by CAP and aCAP certificants to satisfy the 30 PDUs needed to renew their certification every three (3) years. More info.
YCBS 257 Data at Scale (9 CEUs)
Overview of various aspects of large data sets and how they are managed both on site and in the Cloud. Emphasis on hands-on experience from data ingestion to analysis of large data sets, both data-at-rest and data-in-motion (streaming data), including defining Big Data and its 5 V's: Volume, Velocity, Variety, Veracity, and Value.
YCBS 258 Practical Machine Learning (9 CEUs)
This course aims to introduce participants to essential machine learning methods and techniques through an end-to-end machine learning project. Emphasis is placed on practical experience with machine learning using Python programming language, scikit-learn and TensorFlow, as well as on understanding classification and training models. The course will provide an introduction to artificial Neural Networks, deep learning, convolutional and recurrent neural nets and reinforcement learning.
YCBS 299 Data Science Capstone Project (9 CEUs)
Integration and application of knowledge and skills gained during the program through hands-on projects supported by our industry partners to build a full data science pipeline from preparing, analyzing and visualizing data to building and testing models. Communication and presentation of insights and recommendations derived from data analysis using visualization and storytelling techniques.

Contacts

Développement de carrière et perfectionnement professionnel
Tél.: +1 514-398-5454
680, rue Sherbrooke Ouest, bureau 1029 Montréal (Québec)  H3A 2M7
Horaires d'ouverture

Du lundi au vendredi
de 9 h à 17 h

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