COURSE INTRODUCTION

Learn how to analyze data in Python using multi-dimensional arrays in NumPy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more.

COURSE CONTENT

Section 01 - Programming Basics and Data Analytics with Python (Self Learning Curriculum)

• Lesson 01 - Learning Objective
• Lesson 02 - Introduction
• Lesson 03 - Data Wrangling
• Lesson 04 - Exploratory Data Analysis
• Lesson 05 - Model Development
• Lesson 06 - Model Evaluation

Section 02 - Programming Basics and Data Analytics with Python (Live Classes Curriculum)

• Lesson 01 - Course Introduction
• Lesson 02 - Introduction to Programming
• Lesson 03 - Programming Environment Setup
• Lesson 04 - OOPs Concept with Python
• Lesson 05 - Programming Fundamentals of Python
• Lesson 06 - File handling, Exception handling, and Package handling
• Lesson 07 - Data Analytics Overview
• Lesson 08 - 0Statistical Computing
• Lesson 09 - Mathematical Computing using NumPy
• Lesson 10 - Data Manipulation with Pandas
• Lesson 11 - Data visualization with Python
• Lesson 12 - Introduction to Model Building

Section 03 - Practice Projects