Section 1 : Introduction to python
Lecture 1 Course Promo copy
Lecture 2 Thank You 00:01:06 Duration
Lecture 3 How to get 100% from this course 00:00:34 Duration

Section 2 : Setting up environment and jupyter notebook
Lecture 1 Python Environment setup 00:17:13 Duration

Section 3 : Module -2 python Arithmetic operations
Lecture 1 Terminology Alert 00:05:25 Duration
Lecture 2 Arithmetic Operators in python 00:08:42 Duration
Lecture 3 github link 00:02:06 Duration
Lecture 4 Student Community 00:00:59 Duration

Section 4 : module 3- python basics list string dictionary
Lecture 1 Module Intro 00:00:14 Duration
Lecture 2 Terminology Alert 00:01:28 Duration
Lecture 3 Python-Strings 00:08:06 Duration
Lecture 4 Terminology Alert 00:02:27 Duration
Lecture 5 Python-list 00:14:56 Duration
Lecture 6 Python-Dictionary 00:09:08 Duration

Section 5 : Numpy -Array Attributes
Lecture 1 Module Intro 00:01:14 Duration
Lecture 2 Terminology Alert 00:02:33 Duration
Lecture 3 Numpy-Basic array operations 00:07:51 Duration
Lecture 4 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 5 Terminology Alert 00:04:46 Duration
Lecture 6 Numpy-Random-Numbers 00:08:40 Duration
Lecture 7 Terminology Alert 00:04:51 Duration
Lecture 8 Numpy-advanced 00:03:25 Duration

Section 6 : Pandas
Lecture 1 Module Intro 00:01:44 Duration
Lecture 2 Pandas part1 00:06:23 Duration
Lecture 3 pandas part 2 00:05:06 Duration
Lecture 4 pandas part 3 00:07:51 Duration
Lecture 5 pandas part4 00:16:20 Duration

Section 7 : Matplotlib- Introduction
Lecture 1 Matplotlib-Introduction 00:02:45 Duration
Lecture 2 matplotlib1 00:02:52 Duration
Lecture 3 Matplotlib 1 00:03:41 Duration
Lecture 4 Matplotlib1 00:02:10 Duration
Lecture 5 Pandas with matplotlib 00:02:42 Duration
Lecture 6 Matplotlib advanced Exercise 00:18:06 Duration

Section 8 : Introduction to Data Science
Lecture 1 Introduction to Data Science
Lecture 2 Data Science with python Part 1 00:14:05 Duration
Lecture 3 Data Science with python Part 2 00:03:13 Duration
Lecture 4 Data Science with python Part 3
Lecture 5 Data Science with python Part 4 00:01:35 Duration
Lecture 6 Data Exploration Part 1 00:02:42 Duration
Lecture 7 Data Exploration Part 2 00:08:59 Duration
Lecture 8 Data Exploration Part 3 00:03:52 Duration
Lecture 9 T-Test
Lecture 10 T-test in python 00:05:09 Duration
Lecture 11 Z-Test 00:06:58 Duration
Lecture 12 Chi-Square Test 00:07:31 Duration
Lecture 13 Bivariate Exploration 1 00:05:56 Duration
Lecture 14 Bivariate Exploration 2 00:06:23 Duration
Lecture 15 Bivariate Exploration 2 00:04:26 Duration
Lecture 16 Modelling basics 00:09:18 Duration
Lecture 17 what is linear regression 00:04:14 Duration
Lecture 18 Gradient Descent with linear regression 00:07:05 Duration

Section 9 : Create simple machine learning models with sklearn
Lecture 1 sklearn Intro 00:01:08 Duration
Lecture 2 sklearn part 1 00:11:51 Duration
Lecture 3 Sklearn part 2 00:03:34 Duration

Section 10 : Flight Delay Prediction with real world data
Lecture 1 Flight Delay Prediction Introduction 00:08:02 Duration
Lecture 2 Flight Delay Prediction Data Pre-processing 00:17:02 Duration
Lecture 3 Flight Delay Prediction Feature Generation 00:22:43 Duration
Lecture 4 Flight Delay Prediction with Random Forest 00:02:54 Duration
Lecture 5 Flight Delay Prediction final

Section 11 : Anaconda environment and conda cheat sheet
Lecture 1 Optional Anaconda Virtual Environments 00:18:38 Duration

Section 12 : Bonus Lectures
Lecture 1 Playing with python codes 00:00:40 Duration
Lecture 2 Creating dashboards 00:22:17 Duration
Lecture 3 creating charts with python 00:27:44 Duration
Lecture 4 Live video Transformation with python 00:11:11 Duration
Lecture 5 Data Science Interview Questions 00:07:37 Duration