Machine Learning with Python


Machine Learning (ML) is a rapidly growing field that has captured the interest of the global community. Given all the buzz around, it can be difficult to understand what exactly it is. This course will help you grasp what ML is and what it is not, as well as understand the motivations and use cases related to ML. You will see why Python has become the tool of choice for ML, and then use it to solve multiple types of ML problems.

This course features hands-on labs hosted on CENGN's multi-vendor cloud, using the popular Jupyter Notebook web-based interactive development environment. The course culminates with an end-to-end exercise including data cleaning and visualization, problem specification, algorithm selection and results analysis.

This training package includes one attempt for the CENGN Machine Learning With Python exam. Those who successfully complete the exam will earn a CENGN Machine Learning With Python digital badge, which can be posted on LinkedIn and other social media. 

Recommended Prequisites:

  • Moderate background in mathematics, especially statistics
  • Introductory level experience with Python
  • Intermediate level understanding of data analysis

Duration: Learners will need approximately 20-25 hours to complete the course. Learners will have access to the online content and labs for 4 weeks.

Course developed in collaboration with Lighthouse Labs.

Please note: Registration closes a week prior to start date.



This course is supported by SCALE AI. All persons employed in Canada are eligible to benefit from a 50% discount on enrolment fees. Please select the SCALE AI session below and register with your work email address and work mailing address. 


  • Recognize the key concepts, best practices, and applications of machine learning
  • Identify the most widely used machine learning algorithms and discuss their strengths and weaknesses.
  • Describe basic machine learning principles such as classification, regression, clustering, association learning, and dimensionality reduction.
  • Recall Python fundamentals, including basic syntax, variables, and types.
  • Build, train, and evaluate the performance of machine learning models using
  • Python and its associated libraries.
  • Select the appropriate machine learning model for a given problem.
  • Perform exploratory data analysis on a dataset to detect anomalies and to summarize its main characteristics.



  • Software developer/engineer/architect starting with ML
  • Software team lead or manager overseeing ML teams
  • Product manager overseeing an ML product


Delivery Mode

  • Learn on your own schedule with self-paced online training and labs.


Featured Instructor

The CENGN Academy team of subject matter experts will be available to support you while you take this course. We will answer your questions, confirm your labs, and check in with you after your course to assist with your badge exam preparations. Contact details will be provided when the course begins.


This course is offered through B2B Group Training, upon request. Please submit a group training request