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Exploratory Data Analytics is the branch of Data Science that deals with the process of initial investigation and analysis of data to summarise, visualise and draw conclusions towards finding the inferences of the study. Data Forecasting is the process to predict future events based on the analysis of the existing trends shown by the past data. It forms the foundation of Machine Learning and gives a basic insight into how a Machine Learning Algorithm works.

Through the duration of this course, a student gets to learn how to analyse these patterns in data, base their analysis on relevant parameters as per the requirement of the data, forecast future outcomes and step into the world of building Machine Learning alogorithms.

Insights Of The Course:

Introduction to Data Analytics

Introduction to Anaconda and Jupyter. How to install Anaconda.

Introduction to Python  (Basic Functions, Data Structures, STATEMENTS, Packages and modules and scripts) followed by Project 1

Introduction to Python (Defining functions, User Inputs, Reading and Writing files, Arrays) followed by project 2

EDA using the Numpy library

EDA using the Pandas library (SERIES, DATAFRAME, DATATYPE, SLICE, filtering, groupby)

EDA using Matplotlib (Plotting graphs)

EDA using Seaborn (Plotting visually appealing graphs)

Final Project

Industry Experience + Doubts

Technical Interview Training


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