Course Features

  • Course Duration: 30 Days
  • Category:
  • Certificate: Yes
  • Location: Wakad, Pune
  • Lesson: 0
  • Viewers: 2670
  • Prerequisites: Yes
  • Skill Level: Beginner
  • Course Capacity: 10


Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract insights from data in various forms, structured and unstructured, similar to data mining. A Data Scientist person employed to analyze and interpret complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.


  • It’s in Demand
  • Abundance of Positions
  • A Highly Paid Career
  • Data Science is Versatile
  • Data Science Makes Data Better
  • Data Scientists are Highly Prestigious
  • No More Boring Tasks


Introduction to AI & Python

  • Artificial Intelligence training
  • Techniques used for AI
  • Python Basics
  • Getting started with Python
  • Variables, Lists, Vectors, Matrices & Arrays
  • Control Structures – If else, for and while loop
  • Functions & Subroutines
  • Object-oriented Programming
  • Commonly used predefined function in Python
  • Mathematical Computation in Python
  • Miscellaneous Functions & their applications
  • Linear Algebra required for Artificial Intelligence
  • Getting started with PANDAS, QUANDL AND THEANO

Fuzzy Logic

  • Applications of Fuzzy Logic
  • Problem Formulation, Defuzzification & Rule base
  • Membership Functions
  • Defuzzification Methods
  • MAMDANI & SUGENO Methods
  • Tipping Problem Analysis
  • Fuzzy Clustering
  • Fuzzy C Means Clustering

Genetic Algorithm

  • Working with Genetic Algorithm
  • Getting started with Genetic Algorithm
  • Reproduction, Crossover & Mutation
  • Roulette Wheel method of selection
  • Fitness Function
  • Working with GA Examples
  • Optimization using GA
  • Clustering
  • Principal Component Analysis
  • PCA Applications and use cases
  • PCA Implementation

Best Mean Fitting

  • Working with Best Mean Fitting
  • Single Line as Hypothesis Training
  • Using THEANO for best mean fitting

Artificial Neural Network

  • Introduction to Network Architecture & Neuron
  • Designing Neural Network Model
  • Model Representation Methods
  • Single Layer Neural Network
  • Weights & Activation Functions
  • Multilayer Neural Network Architecture
  • Gradient Descent Algorithm
  • Working with theano & Python
  • Training Straight line hypothesis
  • Backward Propagation Training
  • Delta method and Gradient Descent

Support Vector Machine

  • Introduction to SVM
  • Concept of Support Vector Machine
  • Working with scikit learn library
  • SVM Parameters
  • Using Support Vector for Classification
  • Using Support Vector for Regression
  • Character recognition using SVM
  • Natural Language Processing
  • Natural Language Understanding & Generation
  • Using NLTK for extracting data
  • Naive Baiyes Method
  • Sentiment Analysis Example