Data Engineering with Python

Course Curriculum

Chapter 1: Setting up Python

Lecture 1: Downloading and Setting up Python and PyCharm IDE

Lecture 2: Python For Absolute Beginners : Setting up the Environment : Anaconda

Chapter 2: Python Theory

Lecture 1: Python For Absolute Beginners – Variables – Part 1

Lecture 2: Python For Absolute Beginners – Variables – Part 2

Lecture 3: Python For Absolute Beginners – Variables – Part 3

Lecture 4: Python For Absolute Beginners – Lists

Lecture 5: Python For Absolute Beginners – Lists Part 2

Lecture 6: Python For Absolute Beginners – Lists Part 3

Lecture 7: Python – Conditions – if, if-else and elif Part 1

Lecture 8: Python – Conditions – if, if-else and elif Part 2

Lecture 9: Python – Relational Operators Boolean operators –

Lecture 10: Python For beginners – Loops #Iteration

Lecture 11: Python Programming Tutorial : Loops part 1 #Guess the number program

Lecture 12: Python Programming Tutorial : Loops part 2 #Getting a random number

Lecture 13: Python Programming Tutorial : Loops part 1 #Guess the number program #Modified

Lecture 14: Python program to Find the Class Average

Lecture 15: Python : Functions : Demonstration

Lecture 16: Pass by reference vs value

Lecture 17: Python Function – Arguements (Required, Keyword, Default)

Lecture 18: Python: For Loops #Iteration # Repetition

Lecture 19: Python File Handling – Part 1

Chapter 3: Software Design

Lecture 1: Software Design – Problem Solving

Lecture 2: Software Design – Flowcharts – Sequence

Lecture 3: Software Design – Repetition

Lecture 4: Flowcharts Questions and Answers # Problem Solving

Chapter 4: Python Tutorials

Lecture 1: Tutorial 1 – Introduction

Lecture 2: Tutorial 2 – Built-In Functions

Lecture 3: Tutorial 3 – if conditions

Lecture 4: Tutorial 4 – while loops

Lecture 5: Tutorial 5 – for loops and exceptions

Lecture 6: Tutorial 6 – for loop challenge questions

Lecture 7: Tutorial 7 – Guess the Word Game

Lecture 8: Tutorial 8 – Functions (Dragon Kingdom Game)

Chapter 5: Setting up the Environment for Machine Learning

Lecture 1: Downloading and Setting up Anaconda for Machine Learning

Chapter 6: Understanding Data With Statistics & Data Pre-processing

Lecture 1: Understanding Data with Statistics: Reading data from file

Lecture 2: Understanding Data with Statistics: Checking dimensions of Data

Lecture 3: Understanding Data with Statistics: Statistical Summary of Data

Lecture 4: Understanding Data with Statistics: Correlation between attributes

Lecture 5: Data Pre-processing – Scaling with a demonstration in python

Lecture 6: Data Pre-processing – Normalization , Binarization , Standardization in Python

Lecture 7: Feature Selection Techniques : Univariate Selection

Chapter 7: Data Visualization with Python

Lecture 1: Data preparation and Bar Chart

Lecture 2: Data Visualization with Python Histogram , Pie Chart, etc..

Chapter 8: Artificial Neural Networks [Comprehensive Sessions]

Lecture 1: Introduction to Artificial Neural Networks

Lecture 2: Creating the First ANN from Scratch with Python

Lecture 3: Multiple Input Neuron

Lecture 4: Creating a simple layer of neurons, with 4 inputs. # Python # From scratch

Lecture 5: ANN – Illustrative Example

Lecture 6: KERAS Tutorial – Developing an Artificial Neural Network in Python -Step by Step

Lecture 7: Deep Learning -Handwritten Digits Recognition [Step by Step] [Complete Project]

Chapter 9: Naive Bayes Classifier with Python [Lecture & Demo]

Lecture 1: Lecture & Demo: Naive bayes classifier

Chapter 10: Linear regression

Lecture 1: Linear regression

Lecture 2: Univariate Linear Regression Demo [Hands-on] Part 1- Linear Regression

Lecture 3: Univariate Linear Regression Demo [Hands-on] Part 2- Linear Regression

Lecture 4: Multivariate Linear Regression Demo [Hands-on] Linear Regression

Chapter 11: Logistic regression

Lecture 1: Logistic Regression

Chapter 12: Introduction to clustering [K – Means Clustering ]

Lecture 1: What is clustering in Machine Learning

Lecture 2: K – Means Clustering

Lecture 3: [hands-on] K – Means clustering with python step by step implementation

Lecture 4: K-Means clustering – Code walkthrough with Theory & Practical

Chapter 13: Extra Reading

Lecture 1: Neural Network Optimization

Lecture 2: Popular resources from Top Universities of the world

Lecture 3: Machine Learning – Source codes