Introduction to Python and Data Science

Working with Python Data Structures

Control Flow Statements

Functions in Python

File Handling in Python

Regular Expressions

Object Oriented Programming

Advanced-Data Structures in Python

Introduction to SQL and MySQL

Data Creation and Retrieval

Data Filtering

Data Analysis using aggregate functions and group by

Joins and Keys

MySQL Joins

Subqueries and Views

Window/Analytical Functions

Case Study

Introduction to Statistics

Probability Theory

Statistical Inference I

Statistical Inference II

Regression Analysis I

Regression Analysis II

Unleashing the Power of Excel

Data Analysis with MS Excel

Summarizing and Forecasting

Macros and Dashboarding

Excel Project Session

Extracting and Aggregating Pandas

Matplotlib and Seaborn

Plotly and Cuffinks

Introduction to Data Cleaning and Data Types

Exploring and Visualization the missing values

Advanced-Data Cleaning Concepts

Introduction to Feature Engineering

Feature Extraction and Transformation

Feature Selection and Dimensionality Reduction

Modeling with Linear Regression

Evaluating Models & Feature selection

Regularisation Techniques

Modeling with Logisitc Regression

Advanced Model Evaluation Techniques

Introduction to Clustering and K Means

Advanced Clustering Techniques

Introduction to Decision Trees

Implementation of Decision Trees

Introduction to the Concept of Bagging

Introduction to Concept of Random Forest

Introduction to Boosting

Introduction to extreme Gradient Boosting

Introduction to Imbalanced Machine Learning models

Introduction to Recommendation Engines

Introduction to Time Series Analysis

Preprocessing and Visualization of Time Series Data

Time Series Forecasting using ARIMA

Exponential Smoothing Models for Time Series Forecasting

Machine Learning Models for Time Series Forecasting

Time Series Forecasting using Prophet

NLP Fundamentals

Feature Engineering in NLP & Text Classification

Advanced-Data Cleaning for NLP text classification

Feature Extraction & Feature encoding for NLP

Introduction to Word Embeddings

Advanced word embeddings used to solve NLP problems

More about advanced NLP

NLP text classification end to end project from kaggle

Building blocks of Deep Learning

Understanding the Components of a Neural Network

Introduction to Recurrent Neural Networks

Overview of LSTM and GRU

Introduction to Bidirectional Networks

RNN Use Cases in the Industry

Introduction to Convolutional Neural Networks (CNN)

Overview of Transfer Learning

Introduction to Transformers

Overview of AutoEncoders