Data Science and Data Analytics tools

Course outline

This course will give full overview of the Data Science & Data Analytics journey. Participants will learn, how to clean and prepare your data for analysis, perform basic visualization, understand how to model and how to curve-fit your data. In this course participants will learn working of different tolls/libraries for Data Science besides concepts like Algorithm, Probability and Predictive Analytics.

Table of Content

1. 1. Basics of Data Science & Analytics – Introduction
      • What is Data Science and Data Analytics?
      • Supervised & Unsupervised Learning
      • Regression & Classification Problems
      • Artificial Intelligence & Machine Learning Introduction
      • What makes a Machine Learning Expert?
   2. Handling Data
      • Introduction to Data Visualization
      • Processes in Data Science
      • Data Wrangling, Data Exploration, and Model Selection
      • Exploratory Data Analysis or EDA
      • Hypothesis Building and Testing
   3. Programming Language Python  What & Why
   4. Overview of Data Science and Data Analytics tools 
      • Python libraries – SciPy, NumPy, Pandas etc.
      • Tableau
      • Power BI
   5. Understand Algorithm and Probability
   6. Understand Predictive Analytics
   7. Some hands on Data Visualization

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