This course is designed to help students to be industry ready with respect to Machine Learning and Python. Student will be in a position to start delivering in real life industry implementations.

Who should attend

  • Aspiring IT professionals
  • Engineering Students (CSE / IT / Electronics)
  • Developers Willing to learn Python programming and its usage in Machine Learning. Designers/Architects in AI/ML on how to model machine Learning Problem using Python

Pre – Requisite

  • Basic database / UNIX System understanding

Course Detail

  • Python Basics
  • Python and what’s different about it
  • Importance of white space in Python scripts – iPython and Spyder
  • Run Python code: interactively from the Python shell,or running stand-alone Python script files
  • How to import Python modules
  • Expression, Variable and Strings
  • Python data structures including lists, tuples, and dictionaries
  • Functions, Boolean expressions, and looping constructs in Python
  • Loading, examining, and manipulating data
  • Loading Data with Pandas, Working and Saving data using Pandas
  • One and Two dimensional NumPy
  • Basics of Numpy, Seaborn, Scikit learn, Matplotlib
  • Working with Text Files
  • Basics of Data Analytics
  • Types of Analytics – Descriptive, Predictive, Prescriptive
  • Basics of Machine Learning
  • Common Machine Learning Terms – Probability, Mean, Mode, Median, Range
  • Supervised and Unsupervised Learning
  • Linear Regression Theories / Logistic Regression
  • Data Preparation – Dimensionality Reduction (Feature Selection / Feature Extraction ); Principal Component Analysis
  • Data Types – differences between continuous and discrete numerical data, categorical data, and ordinal data
  • Variable selection Methods
  • Classification Models
  • Support Vector Machines
  • Decision Trees
  • Naïve Baise Classifiers
  • Gradient Boosting Decision Tress
  • Random Forest
  • Clustering Models – K Means
  • Evaluation of Models
  • Deployment of Models
  • Developing ML Models using Python Programing
  • Playing with Real life data using Python


30 Hrs.