Data Analytics using Python

Course: Data Analytics using Python

Course Contents

1. Numpy – Handling NUMERICALS

• Handling Arrays

• Creating and Printing of an array

• Basic Operations in Numpy

• Indexing

• Important Mathematical operations using Numpy

2. Data Manipulation with Pandas

• Understanding Series and Data Frames

• Importing and Exporting Data through Excel/CSV Files

• Understanding various Operations on Data

• Indexing, slicing and advanced filtering with Conditional Slicing

• Process of Concatenating and Merging

• Understanding Descriptive Statistics

• Removing Duplicates

• Manipulation of String

• Missing Data Handling

3. DATA VISUALIZATION

Data Visualization using Matplotlib and Pandas

• Introduction to Matplotlib

• Basic Plotting

• Properties of plotting

• About Subplots

• Line plots

• Pie chart and Bar Graph

• Histograms

• Box and Violin Plots

• Scatterplot

4. Case Studies on Exploratory Data Analysis (EDA) and Visualizations

• What is EDA?

• Uni – Variate Analysis

• Bi-Variate Analysis

• More on Seaborn based Plotting Including Pair Plots, Catplot, Heat Maps, Count plot along with matplotlib plots.

5. Unstructured Data Processing

Regular Expressions

• Structured Data and Unstructured Data

• Literals and Meta Characters

• Regular Expressions using Pandas?

• Inbuilt Methods

• Pattern Matching

6. Project On Web Scraping: Data Mining and Exploratory Data Analysis

•  Data Collection

• Data Mining

• Data Pre-processing

• Data Visualization using following data files/images

e.g., Text, CSV, TSV, Excel Files, Matrices, Images

This project shall start from scratch and would involve the collection of Raw Data from different sources. It shall include conversion of the unstructured data to a structured format in order to make it suitable for Machine Learning and NLP models. This project covers the crucial steps of the Data Science, which are mentioned as above.