Machine Learning Foundation

  • This a 2 day most powerful and unique course on Machine learning course covering 360 degree aspects of Machine Learning and Artificial Intelligence for foundation level knowledge . It covers Machine Learning foundation for first 2 day program on understanding concepts on ML and AI with hands-on labs sessions . where you learn how to Train your own model with ML tools.

    • 2 days of instructor-led training
    • Machine learning foundation

    • Understand Machine Learning concepts
    • Differentiate between Supervised, Un-Supervised and Reinforcement learning
    • Understand Federated and semi-supervised learning
    • Understand Deep Learning and AI
    • Understand use cases of ML and AI in various industry
    • Quick hands-on labs with just enough python in 30 mins for ML and AI
    • Hands-on labs sessions on Pandas, Tensorflow, KNN, Scikit learn
    • Run programs on classification, clustering and reinforcement learning
    • Run programs for recommendations , Data visualization and sentiment Analysis

  • This course is developed from a vendor neutral perspective from Cloud Enabled experts, hence single vendor certification is not targeted here. No exams

    • Software developers
    • IT Consultants
    • BigData Developers
    • BigData Administrators
    • Program Managers
    • Anyone Passionate about ML


  • Day 1 & 2 : ML and AI Foundation ( Train Your own Models)
    Module 1 : Demystify Machine Learning and Artificial Intelligence

    • Evolution of Machine Learning
    • Define Machine Learning (ML)
    • Define Supervised Learning
    • Define Un-Supervised Learning
    • Define reinforcement learning
    • Define Semi-supervised Learning
    • Define Federated Learning
    • Understand concepts of AI, Deep Learning and NLP

    Module 2 : Use Cases

    • Machine Learning in Banking and Finance Industry
    • Machine Learning in Healthcare
    • Machine Learning in Transportation
    • Machine Learning in Government
    • Machine Learning in Media and entertainment
    • Top 10 AI predictions
    • What next in AI ?
    • ML and AI industry insights

    Module 3: ML- Prerequisites Refreshers

    • Data Types ( Numerical, categorical and Ordinal)
    • Just enough Python for ML
    • Lab : Simple python exercise
    • Introduction to NumPy and simple lab on numpy
    • Introduction to SciPy and simple lab on Scipy
    • Introduction to Pandas and simple lab exercise
    • Introduction to MatPlotLib and simple lab exercise

    Module 4: Hands on lab Sessions on Machine Learning and AI

    • Classification Lab – Classify images using Tensorflow and visualise using Matplotlib
    • Clustering Lab – Customer segmentation
    • Regression Lab – Predict pricing of house Scikit-learn NumPy and Pandas
    • Recommendation Lab – Provide recommendations using Natural Language Processing using live data of training services company ( using Nltk tool kit)
    • Sentiment Analysis Lab – Movie review ( Positive or negative) using Natural Language Processing
    • Reinforcement Learning Lab – Place agent in one of the room and goal is to reach outside the building
    • Association Lab – Perform Market basket analysis for e-commerce

    • Gives an edge over other professionals in the same field, in term of pay package.
    • Customer are transitioning to AI enabled organization  .
    • Helpful for People are trying to transition to  data scientist  roles from software engineer
    • The tool training helps to speak more confidently about this technology at my company when networking with others.

  • For India :  email us at anil.bidari@thecloudenabled.com

    For Singapore  :   email us at anil.bidari@thecloudenabled.com