Establish your mastery of data science and analytics techniques using Python by enrolling in this Data Science with Python course. 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, so jumpstart your career with this interactive, hands-on, Data Science with Python course.

Interactive learning with Jupyter notebooks integrated labs

Dedicated mentoring session from faculty of industry experts

Delivery Mode

Blended

This course consists of self-paced learning and live virtual classroom

Prerequisites

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

Target Audience

Analytics professionals willing to work with Python

Software and IT professionals interested in analytics

Anyone with a genuine interest in data science

Key Learning Outcomes

This Python for Data Science training course will enable you to:

Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing; and the basics of statistics

Understand the essential concepts of Python programming such as datatypes, tuples, lists, dicts, basic operators, and functions

Perform high-level mathematical computations using the NumPy and SciPy packages and their large library of mathematical functions

Perform data analysis and manipulation using data structures and tools provided in the Pandas package

Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline

Use the Scikit-Learn package for natural language processing and matplotlib library of Python for data visualization

Course Curriculum

Lesson 00 - Course Overview

Course Overview

Lesson 01 - Data Science Overview

Introduction to Data Science

Different Sectors Using Data Science

Purpose and Components of Python

Quiz

Key Takeaways

Lesson 02 - Data Analytics Overview

Data Analytics Process

Knowledge Check

Exploratory Data Analysis (EDA)

Quiz

EDA-Quantitative Technique

EDA - Graphical Technique

Load 7 More

Data Analytics Communication

Data Types for Plotting

Data Types and Plotting

Quiz

Key Takeaways

Knowledge Check

Lesson 03 - Statistical Analysis and Business Applications

Introduction to Statistics

Statistical and Non-statistical Analysis

Major Categories of Statistics

Statistical Analysis Considerations

Population and Sample

Statistical Analysis Process

Load 10 More

Dispersion

Knowledge Check

Histogram

Knowledge Check

Testing

Knowledge Check

Correlation and Inferential Statistics

Quiz

Key Takeaways

Lesson 04 - Python Environment Setup and Essentials

Anaconda

Installation of Anaconda Python Distribution (contd.)

Data Types with Python

Basic Operators and Functions

Quiz

Key Takeaways

Lesson 05 - Mathematical Computing with Python (NumPy)

Introduction to NumPy

Activity-Sequence it Right

Demo 01-Creating and Printing an ndarray

Knowledge Check

Class and Attributes of ndarray

Basic Operations

Load 9 More

Copy and Views

Mathematical Functions of NumPy

Assignment 01: Evaluate the datasets containing GDPs of different countries

Demo: Assignment 01

Assignment 02: Evaluate the datasets of Summer Olympics, 2012

Demo: Assignment 02

Quiz

Key Takeaways

Lesson 06 - Scientific computing with Python (SciPy)

Introduction to SciPy

SciPy Sub Package - Integration and Optimization

Knowledge Check

SciPy sub package

Demo - Calculate Eigenvalues and Eigenvector

Knowledge Check

Load 7 More

Assignment 01: Use SciPy to solve a linear algebra problem

Demo: Assignment 01

Assignment 02: Use SciPy to define 20 random variables for random values

Demo: Assignment 02

Quiz

Key Takeaways

Lesson 07 - Data Manipulation with Pandas

Introduction to Pandas

Knowledge Check

Understanding DataFrame

View and Select Data Demo

Missing Values

Data Operations

Load 10 More

File Read and Write Support

Knowledge Check-Sequence it Right

Pandas Sql Operation

Assignment 01: Analyze the Federal Aviation Authority(FAA) dataset using Pandas

Demo: Assignment 01

Assignment 02: Analyze the dataset in csv format given for fire department

Demo: Assignment 02

Quiz

Key Takeaways

Lesson 08 - Machine Learning with Scikit–Learn

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

Load 10 More

Scikit-Learn

Knowledge Check

Supervised Learning Models - Linear Regression

Supervised Learning Models - Logistic Regression

Unsupervised Learning Models

Pipeline

Model Persistence and Evaluation

Knowledge Check

Assignment 01: Evaluate a dataset to find the features or media channels used by a firm and sales figures for each channel

Demo: Assignment 01

Assignment 02: Analyze a dataset to find the features and response label of it

Demo: Assignment 02

Quiz

Key Takeaways

Lesson 09 - Natural Language Processing with Scikit Learn

NLP Overview

NLP Applications

Knowledge Check

NLP Libraries-Scikit

Extraction Considerations

Scikit Learn-Model Training and Grid Search

Load 6 More

Demo Assignment 01

Assignment 02: Analyze the sentiment dataset using NLP

Demo: Assignment 02

Quiz

Key Takeaway

Load 3 More

Lesson 11 - Web Scraping with BeautifulSoup

Web Scraping and Parsing

Knowledge Check

Understanding and Searching the Tree

Navigating options

Demo3 Navigating a Tree

Knowledge Check

Load 8 More

Parsing and Printing the Document

Assignment 01: Scrape the website page to perform some tasks

Demo: Assignment 01

Assignment 02: Scrape the website page to perform some tasks

Demo: Assignment 02

Quiz

Key takeaways

Lesson 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

Knowledge Check

Python Integration with Spark using PySpark

Load 8 More

Knowledge Check

Assignment 01: Determine the word count for Amazon dataset

Demo: Assignment 01

Assignment 02: Count and display all airports present in New York using PySpark

Demo : Assignment 02

Quiz

Key takeaways

Program Features

4 industry-based course-end projects

Interactive learning with Jupyter notebooks integrated labs

Dedicated mentoring session from faculty of industry experts