What you'll get

  • Govt. Verified Certification
  • Job Credibility
  • Certification Valid for Life
  • Lifetime Access To E-learning

Description

Course content

Total: 106 lectures
  • Installation of Python and Anaconda
  • Python Introduction
  • Variables in Python
  • Numeric Operations in Python
  • Logical Operations
  • If else Loop
  • for while Loop
  • Functions
  • String Part1
  • String Part2
  • List Part1
  • List Part2
  • List Part3
  • List Part4
  • Tuples
  • Sets
  • Dictionaries
  • Comprehensions
  • Introduction
  • Numpy Operations Part1
  • Numpy Operations Part2
  • Introduction
  • Series
  • DataFrame
  • Operations Part1
  • Operations Part2
  • Indexes
  • loc and iloc
  • Reading CSV
  • Merging Part 1
  • groupby
  • Merging Part2
  • Pivot Table
  • Linear Algebra: Vectors
  • Linear Algebra: Matrix Part1
  • Linear Algebra: Matrix Part2
  • Linear Algebra: Going From 2D to nD Part1
  • Linear Algebra: 2D to nD Part2
  • Inferential Statistics
  • Probability Theory
  • Probability Distribution
  • Expected Values Part1
  • Expected Values Part2
  • Without Experiment
  • Binomial Distribution
  • Commulative Distribution
  • PDF
  • Normal Distribution
  • z Score
  • Sampling
  • Sampling Distribution
  • Central Limit Theorem
  • Confidence Interval Part1
  • Confidence Interval Part2
  • Introduction
  • NULL and Alternate Hypothesis
  • Examples
  • One/Two Tailed Tests
  • Critical Value Method
  • z Table
  • Examples
  • More Examples
  • p Value
  • Types of Error
  • t- distribution Part1
  • t- distribution Part2
  • 7
  • Data Visualization
  • Matplotlib
  • Seaborn
  • Case Study
  • Seaborn on Time Series Data
  • Introduction
  • Data Sourcing and Cleaning part1
  • Data Sourcing and Cleaning part2
  • Data Sourcing and Cleaning part3
  • Data Sourcing and Cleaning part4
  • Data Sourcing and Cleaning part5
  • Data Sourcing and Cleaning part6
  • Data Cleaning part1
  • Data Cleaning part2
  • Univariate Analysis Part1
  • Univariate Analysis Part2
  • Segmented Analysis
  • Bivariate Analysis
  • Derived Columns
  • Installing Anaconda & using Jupyter Notebook
  • Introduction to Machine Learning
  • Types of Machine Learning
  • Introduction to Linear Regression (LR)
  • How LR Works?
  • Some Fun With Maths Behind LR
  • R Square
  • LR Case Study Part1
  • LR Case Study Part2
  • LR Case Study Part3
  • Residual Square Error (RSE)
  • Investment Project Brief
  • Investment Project_Data Cleaning Part 1
  • Investment Project_Data Cleaning - Part 2
  • Investment Project_Funding_Country_Sector Analysis Part 1
  • Investment Project_Funding_Country_Sector Analysis Part 2
  • Problem Statement
  • Lending Club Default Analysis - Data Understanding and Data Cleaning
  • Data Analysis - Univariate & Bivariate Analysis
  • Segmented Univariate Analysis

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