Breaking into AI and Machine Learning

Through a series of hands-on projects, you too can gain the skills necessary to start applying AI/ML to your own problems.

Are you a software engineer or tester who would like to break into AI and machine learning (ML), but don't know how to get started? One of the best ways to get into ML is by designing and completing small projects. Although you will ultimately need to understand the fundamentals of AI/ML, there's no reason why you can't learn foundational terms, concepts and principles as you put them into practice.

Join Tariq King as he introduces you to the world of applied machine learning. Tariq will guide you through a series of ML projects end-to-end, enabling you to gain experience with creating and loading training data, summarizing and visualizing the datasets, evaluating various ML algorithms, and using the trained models to make predictions. Leave the session motivated and equipped to start using ML in your own projects. This is an introductory session for participants of all skill levels, so you don't need to know how the algorithms work, be a python programmer, or ML expert to get started.

Participants will use a variety of tools and frameworks to learn how to apply AI and machine learning techniques including machine vision, reinforcement learning, and natural language processing. Set up time will be kept at a minimal by leveraging Jupyter Notebooks in the cloud.


Related Sessions


  • Tutorial
  • Keynote
  • Talk
  • Workshop
  • Combo
  • Bonus
  • Active
  • Social
  • Virtual Pass icon
    Virtual Pass Session

105-minute Workshop

10:45 a.m. – 12:30 p.m. Creative Space Room - Track 9: Workshops & Open Space Equipment required

25-minute Talk

Virtual Pass session
4:00 p.m. – 4:45 p.m. Room F1 - Track 1: Talks

Full-Day Tutorial (6 hours)

8:30 a.m. – 4:30 p.m. F-,E- & D-Rooms Equipment required

45-minute Keynote

Virtual Pass session
9:15 a.m. – 10:15 a.m. Room F1+F2+F3 - Plenary

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