Data Analytics Syllabus

1.) Python Fundamentals for Data Analysis

o Python Data Structure

o Control Statement

o Functions

o Object Oriented Programming concept using Classes

o Objects and Methods

o Exceptions Handling

o Implementation of User Define modules and Packages

o File Handling using python

2.) Introduction to Data understanding and preprocessing

o Knowledge domains of Data Analysis

o Understanding structured and unstructured data

o Data Analysis process

o Dataset generation

o Importing Dataset: Importing and Exporting Data

o Basic Insights from Datasets

o Cleaning and Preparing the Data: Identify and Handle Missing Values

3.) Data Processing and Visualization

o Data Formatting

o Exploratory Data Analysis

o Filtering and hierarchical indexing using Pandas

o Data Visualization:-

§ Basic Visualization Tools

§ Specialized Visualization Tools

§ Seaborn Creating and Plotting Maps

4.) Mathematical and Scientific applications for Data Analysis

o Numpy and Scipy Package

o Understanding and creating N-dimensional arrays

o Basic indexing and slicing

o Boolean indexing

o Fancy indexing

o Universal functions

o Data processing using arrays

o File input and output with arrays

5.) Analysing Web Data

o Combing and merging data sets

o Reshaping and pivoting

o Data transformation

o String Manipulation

6.) Model Development and Evaluation

o Introduction to machine learning

o Supervised

o Unsupervised Learning

o Model development using Linear Regression

o Model Visualization

o Prediction and Decision Making

o Model Evaluation

o Over-fitting

o Under-fitting and Model Selection