Advanced Machine Learning



Advanced Machine Learning

This programme develops Machine Learning skills for solving real-life problems in the new digital world.  Machine Learning combines computer science and statistics to analyse raw real-time data, identify trends, and make predictions.  The participants will explore key techniques and tools to build Machine Learning solutions for businesses.

This programme is for professionals involved in Machine Learning projects and initiatives.  The programme is also well suited for the youth, students, and graduates who wish to pursue a professional career in Machine Learning.

Duration: 8 weeks.

Mode:  Course are facilitated by our expert faculty via our video conferencing platform.

Programme Content

  • An introduction to terminology, definitions, and concepts of Machine Learning
  • The evolution and future of Machine Learning
  • Introduction to relevant Machine Learning techniques, decision trees, algorithms, datasets, and statistical techniques
  • Overview of principles, techniques and business applications of Machine Learning
  • Supervised and Unsupervised Learning
  • Classification, regression, and clustering
  • Performance evaluation of Supervised and Unsupervised Learning algorithms
  • Deep Learning for business
  • Best practices in Machine Learning
  • Introduction to Artificial Intelligence, Robotics, Data Science and Blockchain
  • Machine Learning challenges and the future

What will you learn

  • Python Fundamentals
  • Use concepts from probability, statistics, linear algebra, calculus
  • Functional tools for prediction of unseen data
  • Machine Learning algorithms for classification, regression and clustering
  • Optimization workings of machine learning algorithms
  • 12+ projects on Industrial applications of Machine Learning
  • Property price prediction – Regression case study
  • Wine Quality Testing – Classification case study
  • Time Series Analysis

Course Breakdown

    Session 1 – Fundamental concepts, Mathematical and statistical analysis techniques
    Session 2 – Understanding and Analyzing Data
    Session 3 – Introduction to Machine Learning with Python
    Session 4 – Exploratory data analysis
    Session 5 – Supervised learning algorithms I
    Session 6 – Supervised learning algorithms-II
    Session 7 – Unsupervised learning algorithms
    Session 8 – Model selection and evaluation techniques
    Session 9 – Reinforcement Learning
    Session 10 – Model Selection and Boosting
    Session 11 – Time Series Analysis
    Session 12 – Deep Learning Basics
    Session 13 – Neural Network
    Session 14 – Capstone Project Part – 1
    Session 15 – Capstone Project Part – 2

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South Africa




R       9 900.00

₹     82 000.00

₦   287 100.00

$           695.00

** Pricing is subject to lockdown taxes and foreign exchange rates.



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