ETL TESTING

ETL TESTING

Course Features

  • Location: Wakad, Pune
  • Lesson: 0
  • Viewers: 2671
  • Prerequisites: Yes
  • Skill Level: Beginner
  • Course Capacity: 10

WHAT IS DATA SCIENCE?

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.

ADVANTAGES OF DATA SCIENCE

  • 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

COURSE CONTENT

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