Data Science with Python

User Rating

Data science is the newest in the industry and very much popular among the people who wants to build their career as Business Analyst or Data Science Engineer. You’ll learn the essential concepts of Python programming and gain in-depth knowledge of data analytics, machine learning, data visualization, web scraping, and natural language processing. Python is a required skill for many data science positions.


Avg Salary Hike


Job Openings


Course Curriculum


  1. People should know the basics of Python and any programming knowledge.

To best understand the Data Science with Python course, it is recommended that you begin with these courses:

  • Python Basics
  • Math Refresher
  • Data Science in Real Life
  • Statistics Essentials for Data Science

CH 01 – Overview

·         Introduction and basics of Data Science.

·         Python Basics Refresher.

CH 02 – Data Analytics Overview

·         Data Analytics Process

·         Knowledge Check

·         Exploratory Data Analysis (EDA)

·         Quiz

·         EDA-Quantitative Technique

·         EDA - Graphical Technique

·         Data Analytics Conclusion or Predictions

·         Data Analytics Communication

·         Data Types for Plotting

·         Data Types and Plotting

CH 03 – Statistics Overview

·         Introduction to Statistics

·         Statistical and Non-statistical Analysis

·         Major Categories of Statistics

·         Statistical Analysis Considerations

·         Population and Sample

·         Statistical Analysis Process

·         Data Distribution

·         Dispersion

·         Histogram

·         Testing

·         Correlation and Inferential Statistics

Ch 04 – Environment Setup

·         Anaconda

·         Installation of Anaconda Python Distribution (contd.)

·         Data Types with Python

·         Basic Operators and Functions


Ch 05 – Mathematical Computation with Python

·         Introduction to Numpy

·         Activity-Sequence it Right

·         Class and Attributes of ndarray

·         Basic Operations

·         Activity-Slice It

·         Copy and Views

·         Mathematical Functions of Numpy

CH 06 – Scientific Computing with Python

·         Introduction to SciPy

·         SciPy Sub Package - Integration and Optimization

·         SciPy sub package

·         Demo - Calculate Eigenvalues and Eigenvector

·         SciPy Sub Package - Statistics, Weave and IO

CH 07 – Data Manipulation with Pandas

·         Introduction to Pandas

·         Understanding DataFrame

·         View and Select Data Demo

·         Missing Values

·         Data Operations

·         File Read and Write Support

·         Knowledge Check-Sequence it Right

·         Pandas Sql Operation

CH 08 – Machine Learning

·         Machine Learning Approach

·         Understand data sets and extract its features

·         Identifying problem type and learning model

·         How it Works

·         Train, test and optimizing the model

·         Supervised Learning Model Considerations

·         Supervised Learning Models - Linear Regression

·         Supervised Learning Models - Logistic Regression

·         Unsupervised Learning Models

·         Pipeline

·         Model Persistence and Evaluation

CH 09 – Natural Language Processing( NLP)

·         NLP Overview

·         NLP Applications

·         NLP Libraries-Scikit

·         Extraction Considerations

CH 10 – Data Visualization in Python using MatPlotLib

·         Introduction to Data Visualization

·         Line Properties

·         (x,y) Plot and Subplots

·         Types of Plots

Ch 11- Web Scrapping with BeautifulSoup

Web Scraping and Parsing

·         Understanding and Searching the Tree

·         Navigating options

·         Demo3 Navigating a Tree

·         Modifying the Tree

·         Parsing and Printing the Document

CH 12 -Python Integration with Hadoop MapReduce and Spark

·         Why Big Data Solutions are Provided for Python0

·         Hadoop Core Components

·         Python Integration with HDFS using Hadoop Streaming

·         Demo 01 - Using Hadoop Streaming for Calculating Word Count

·         Python Integration with Spark using PySpark

·         Demo 02 - Using PySpark to Determine Word Count

still wondering what to do!

Get a Free Counselling

Click Here to Contact Us