Applied Data Analytics with Python and SQL

This course is part of Applied Data Analytics Specialization

Instructor: Edureka

What you'll learn

Write Python programs using core concepts like variables, data types, and control flow.
Implement NumPy and Pandas to analyze and process large datasets efficiently and accurately.
Create insightful data visualizations with Matplotlib, Seaborn, and Plotly for effective reporting.
Execute SQL queries to retrieve, manage, and analyze data from relational databases accurately.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

Build your subject-matter expertise

This course is part of the Applied Data Analytics Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 4 modules in this course

Unlock the power of Applied Data Analytics with Python and SQL, gaining hands-on experience in data manipulation, querying, and analysis. This course will teach you how to efficiently use Python for processing and analyzing data, while leveraging SQL to manage and query databases. You'll develop the skills needed to extract meaningful insights and apply data-driven solutions to real-world challenges, preparing you to make informed decisions in any industry.

By the end of this course, you’ll be able to: - Categorize Python tokens and different data types used in Python. - Implement conditional statements to control the flow of execution in Python programs. - Leverage Pandas and NumPy for effective data manipulation, cleaning, and analysis. - Explore and apply SQL to retrieve and manage data in relational databases. This course is designed for beginners, data enthusiasts, and aspiring data scientists who want to build a strong foundation in Python programming and modeling data. No prior programming experience is required, although familiarity with the basics of RDBMS and programming concepts will be helpful. Join us to start your journey into data analysis and programming with Python!

This module is designed to help learners take a significant step towards launching their careers in data analytics. In the first week, we'll explore how Python programming concepts that are essential for creating efficient programs. Additionally, we'll delve into the role of pre-defined Python features in data analysis. Let's get started!

What's included

38 videos8 readings5 assignments3 discussion prompts

38 videosTotal 190 minutes

Course Introduction6 minutesPreview module
Programming Languages and Myths6 minutes
Python for AI/ML - Code Simplicity4 minutes
Python for AI/ML - Ease of Learning4 minutes
Identifiers in Python5 minutes
Literals in Python7 minutes
Arithmetic, Comparison, Logical, and Assignment Operators6 minutes
Bitwise, and Membership Operators6 minutes
Python Token Types5 minutes
Boolean Operators in Conditional Statement3 minutes
AND, OR, NOT in Python3 minutes
Working with Dictionaries3 minutes
Manipulating Dictionary4 minutes
Tuples in Python4 minutes
Working with Strings in Python4 minutes
Managing Strings3 minutes
Operations on String4 minutes
Creating Lists3 minutes
Immutable and Mutable Data Types5 minutes
Operations Performed on Lists6 minutes
Sets 6 minutes
Manipulating Sets 1 minute
Exploring Python's Built-in Functions5 minutes
Conditional Statement - if condition3 minutes
Conditional Statement - if else condition4 minutes
Initializing For loop6 minutes
Break, Continue and Pass Statement4 minutes
Validating Prime Numbers3 minutes
Mastering the While Loop in Python6 minutes
Opening Files4 minutes
File Operations5 minutes
Global vs. Local Variables in Python7 minutes
Introduction to Lambda Functions in Python6 minutes
Built-in Modules 5 minutes
Standard Modules5 minutes
Creating User Defined Functions5 minutes
Functions with Multiple Parameters4 minutes
Summary of Python Essentials2 minutes

8 readingsTotal 80 minutes

Welcome to Applied Data Analytics with Python and SQL10 minutes
Starting with Python10 minutes
An Introduction to Python Data Types10 minutes
Built-in Functions in Python10 minutes
Conditional Statements and For Loop in Python10 minutes
Control Flow with Python: break, continue, and pass Statements10 minutes
Lambda Functions in Python10 minutes
File Handling with Python10 minutes

5 assignmentsTotal 42 minutes

Knowledge Check: Python Essentials for Programming30 minutes
Practice Quiz : Python Programming Basics3 minutes
Practice Quiz : Working with Data Types in Python3 minutes
Practice Quiz : Conditional and Control Flow Statements3 minutes
Practice Quiz : Handling Files and File Operations3 minutes

3 discussion promptsTotal 30 minutes

Introduce Yourself10 minutes
Differences in Sets, Tuples and Dictionary10 minutes
Have You Worked on Other Programming Language apart for Python10 minutes

During week two of the course, Learners will be taught how to handle data with NumPy and Pandas in various formats while developing skills to represent data visually using different types of charts and graphics.

What's included

19 videos5 readings4 assignments

19 videosTotal 91 minutes

Introduction to NumPy in Python5 minutesPreview module
Hands-On with NumPy4 minutes
Introduction to Pandas in Python4 minutes
Working with Pandas Series5 minutes
Understanding Pandas DataFrames4 minutes
Data Manipulation with Pandas4 minutes
Combining Datasets with Pandas6 minutes
Matplotlib Library5 minutes
Plotting Charts4 minutes
Plotting Histogram and Box Plot3 minutes
Plotting Multiple Charts6 minutes
Introduction to Seaborn - Scatter Plot6 minutes
Seaborn Basic Charts6 minutes
Seaborn - HeatMap Manipulation2 minutes
Seaborn : Flights Dataset4 minutes
Seaborn: Gaining Insights in Flight Data5 minutes
Visualizing Charts with Plotly4 minutes
Customizing different charts in Plotly5 minutes
Summary of Exploring with NumPy and Pandas 1 minute

5 readingsTotal 60 minutes

NumPy in Python10 minutes
Getting Started with Pandas10 minutes
Data Visualization Fundamentals20 minutes
Data Visualization with Matplotlib10 minutes
Visualization with Seaborn10 minutes

4 assignmentsTotal 39 minutes

Knowledge Check: NumPy, Pandas and Data Visualization Libraries30 minutes
Practice Quiz : Working with NumPy3 minutes
Practice Quiz : Handling Data using Pandas3 minutes
Practice Quiz : Visualizing Data in Python3 minutes

In this module, learners will explore methods for gathering information from various sources on the internet. They will utilize different Python libraries to process and organize the data for thorough evaluation, as well as connect MS SQL Server with Python.

What's included

33 videos4 readings5 assignments

33 videosTotal 154 minutes

What is Web Scraping?6 minutesPreview module
Web Scraping Process Flow5 minutes
Managing Data6 minutes
Beautiful Soup4 minutes
Demonstration of Beautiful Soup4 minutes
Demonstration of Scrapy3 minutes
What is SQL?4 minutes
Operation on Keys5 minutes
Normalization in Databases4 minutes
Types of Normalization 1 NF2 minutes
Types of Normalization 2 NF1 minute
Types of Normalization 3 NF4 minutes
Types of Normalization 4 NF2 minutes
Types of Normalization 5 NF3 minutes
Installation of MS SQL Server6 minutes
DDL Commands5 minutes
DQL Commands6 minutes
DML Commands6 minutes
DCL Commands4 minutes
TCL Commands6 minutes
Setting Up SQL Server4 minutes
Managing Foreign Key 3 minutes
Inserting Data6 minutes
Deleting Data2 minutes
Alter Command4 minutes
Setting up Transaction3 minutes
Connecting with Database6 minutes
Creating Table7 minutes
Inserting Data 6 minutes
Selecting Data1 minute
Updating Records4 minutes
Deleting Records4 minutes
Summary of Web Scraping and SQL1 minute

4 readingsTotal 40 minutes

Web Scraping Best Practices10 minutes
Difference Between MS SQL Server and MySQL 10 minutes
SQL Commands10 minutes
Python with Microsoft SQL Server10 minutes

5 assignmentsTotal 42 minutes

Knowledge Check : SQL, Normalizations and Web Scraping with Python30 minutes
Practice Quiz : Web Scraping with Python3 minutes
Practice Quiz : SQL and Normalization3 minutes
Practice Quiz : Operations on SQL3 minutes
Practice Quiz : Integrating SQL with Python3 minutes

This module is designed to assess an individual on the various concepts and teachings covered in this course. Evaluate your knowledge with a comprehensive graded quiz on Python programming concepts, Data manipulation with NumPy and Pandas with Web-Scraping with Python