Which platform is used to perform coding operation?

The course utilizes Google Colab and MS SQL Server as the primary platform for coding operations. Learners may also use integrated development environments (IDEs) like Jupyter Notebook, PyCharm, Spyder, or VS Code for more extensive coding projects if desired.

Which softwares are needed before starting this course?

Install MS SQL Server and required Python libraries with corresponding IDE's such as PyCharm, Spyder, VS Code etc.

Do I need prior programming or database experience?

No prior experience is required; the course starts with fundamentals and builds up step by step.

Can I use these skills in my job or further study?

Yes, the skills are practical for entry-level analytics roles and form a foundation for advanced study in data science.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Applied Data Analytics with Python and SQL

Q: Who Should Take This Course?

This course is designed for:Freshers looking to enter the fields of data analysis, data science, or artificial intelligence.Individuals with a keen interest in programming who want to enhance their technical skills.Professionals seeking to upskill in Python and data manipulation with SQL for practical applications in their careers.Anyone curious about data and eager to learn how to analyze and visualize it effectively. Whether you're starting your tech journey or looking to build a strong foundation, this course will guide you through the essentials of Python and SQL.

This course is part of Applied Data Analytics Specialization

Instructor: Edureka

1,671 already enrolled

Included with

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4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

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.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments

Taught in English

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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

There are 4 modules in this course

Learn how to work with data using Python and SQL in a practical, project-based course designed to give you relevant, industry-ready skills. You’ll gain hands-on experience manipulating, querying, and analyzing large datasets preparing you to solve real-world data challenges in business, science, or technology.

By the end of this course, you’ll know how to: - Process and analyze data efficiently using Python, with a focus on Pandas and NumPy for manipulation and cleaning. - Write SQL queries to retrieve, filter, and aggregate data in relational databases. - Handle data files (CSV, Excel, JSON) and automate common data tasks for faster, repeatable analysis. - Visualize and report insights from your data to support decision-making. This course is designed for beginners, data enthusiasts, and aspiring data analysts and scientists. No prior programming experience is required, but some familiarity with databases or basic computing concepts will help you progress. You’ll finish with solid skills in Python scripting, SQL, and data analysis, giving you a strong foundation for further study or entry-level roles in data-driven industries.

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 videos Total 190 minutes

Course Introduction 6 minutes
Programming Languages and Myths 7 minutes
Python for AI/ML - Code Simplicity 4 minutes
Python for AI/ML - Ease of Learning 5 minutes
Identifiers in Python 5 minutes
Literals in Python 7 minutes
Arithmetic, Comparison, Logical, and Assignment Operators 6 minutes
Bitwise, and Membership Operators 6 minutes
Python Token Types 5 minutes
Boolean Operators in Conditional Statement 4 minutes
AND, OR, NOT in Python 4 minutes
Working with Dictionaries 4 minutes
Manipulating Dictionary 5 minutes
Tuples in Python 4 minutes
Working with Strings in Python 5 minutes
Managing Strings 4 minutes
Operations on String 5 minutes
Creating Lists 4 minutes
Immutable and Mutable Data Types 5 minutes
Operations Performed on Lists 6 minutes
Sets 7 minutes
Manipulating Sets 1 minute
Exploring Python's Built-in Functions 5 minutes
Conditional Statement - if condition 3 minutes
Conditional Statement - if else condition 5 minutes
Initializing For loop 7 minutes
Break, Continue and Pass Statement 4 minutes
Validating Prime Numbers 4 minutes
Mastering the While Loop in Python 6 minutes
Opening Files 5 minutes
File Operations 6 minutes
Global vs. Local Variables in Python 8 minutes
Introduction to Lambda Functions in Python 7 minutes
Built-in Modules 6 minutes
Standard Modules 6 minutes
Creating User Defined Functions 6 minutes
Functions with Multiple Parameters 4 minutes
Summary of Python Essentials 2 minutes

8 readings Total 80 minutes

Welcome to Applied Data Analytics with Python and SQL 10 minutes
Starting with Python 10 minutes
An Introduction to Python Data Types 10 minutes
Built-in Functions in Python 10 minutes
Conditional Statements and For Loop in Python 10 minutes
Control Flow with Python: break, continue, and pass Statements 10 minutes
Lambda Functions in Python 10 minutes
File Handling with Python 10 minutes

5 assignments Total 42 minutes

Practice Quiz : Python Programming Basics 3 minutes
Practice Quiz : Working with Data Types in Python 3 minutes
Practice Quiz : Conditional and Control Flow Statements 3 minutes
Practice Quiz : Handling Files and File Operations 3 minutes
Knowledge Check: Python Essentials for Programming 30 minutes

3 discussion prompts Total 30 minutes

Introduce Yourself 10 minutes
Differences in Sets, Tuples and Dictionary 10 minutes
Have You Worked on Other Programming Language apart for Python 10 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 videos Total 91 minutes

Introduction to NumPy in Python 6 minutes
Hands-On with NumPy 5 minutes
Introduction to Pandas in Python 4 minutes
Working with Pandas Series 5 minutes
Understanding Pandas DataFrames 5 minutes
Data Manipulation with Pandas 4 minutes
Combining Datasets with Pandas 6 minutes
Matplotlib Library 5 minutes
Plotting Charts 5 minutes
Plotting Histogram and Box Plot 3 minutes
Plotting Multiple Charts 6 minutes
Introduction to Seaborn - Scatter Plot 6 minutes
Seaborn Basic Charts 6 minutes
Seaborn - HeatMap Manipulation 2 minutes
Seaborn : Flights Dataset 5 minutes
Seaborn: Gaining Insights in Flight Data 5 minutes
Visualizing Charts with Plotly 5 minutes
Customizing different charts in Plotly 6 minutes
Summary of Exploring with NumPy and Pandas 2 minutes

5 readings Total 60 minutes

NumPy in Python 10 minutes
Getting Started with Pandas 10 minutes
Data Visualization Fundamentals 20 minutes
Data Visualization with Matplotlib 10 minutes
Visualization with Seaborn 10 minutes

4 assignments Total 39 minutes

Practice Quiz : Working with NumPy 3 minutes
Practice Quiz : Handling Data using Pandas 3 minutes
Practice Quiz : Visualizing Data in Python 3 minutes
Knowledge Check: NumPy, Pandas and Data Visualization Libraries 30 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 videos Total 155 minutes

What is Web Scraping? 6 minutes
Web Scraping Process Flow 5 minutes
Managing Data 6 minutes
Beautiful Soup 5 minutes
Demonstration of Beautiful Soup 5 minutes
Demonstration of Scrapy 3 minutes
What is SQL? 5 minutes
Operation on Keys 5 minutes
Normalization in Databases 4 minutes
Types of Normalization 1 NF 3 minutes
Types of Normalization 2 NF 2 minutes
Types of Normalization 3 NF 5 minutes
Types of Normalization 4 NF 2 minutes
Types of Normalization 5 NF 4 minutes
Installation of MS SQL Server 6 minutes
DDL Commands 6 minutes
DQL Commands 6 minutes
DML Commands 7 minutes
DCL Commands 5 minutes
TCL Commands 7 minutes
Setting Up SQL Server 4 minutes
Managing Foreign Key 3 minutes
Inserting Data 7 minutes
Deleting Data 3 minutes
Alter Command 5 minutes
Setting up Transaction 4 minutes
Connecting with Database 7 minutes
Creating Table 7 minutes
Inserting Data 7 minutes
Selecting Data 1 minute
Updating Records 4 minutes
Deleting Records 4 minutes
Summary of Web Scraping and SQL 1 minute

4 readings Total 40 minutes

Web Scraping Best Practices 10 minutes
Difference Between MS SQL Server and MySQL 10 minutes
SQL Commands 10 minutes
Python with Microsoft SQL Server 10 minutes

5 assignments Total 42 minutes

Practice Quiz : Web Scraping with Python 3 minutes
Practice Quiz : SQL and Normalization 3 minutes
Practice Quiz : Operations on SQL 3 minutes
Practice Quiz : Integrating SQL with Python 3 minutes
Knowledge Check : SQL, Normalizations and Web Scraping with Python 30 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

What's included

1 video1 reading1 assignment1 discussion prompt

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Instructor

Edureka

157 Courses 146,905 learners

Offered by

Edureka

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Frequently asked questions

This course offers a thorough practical application of Python and SQL. Created for Python enthusiasts, it focuses on hands-on skills for manipulating and analyzing data, allowing students to address actual data problems.

Learners will delve into the basics of Python and utilize tools such as NumPy and Pandas for effective data management. They will additionally make use of visualization tools like Matplotlib, Seaborn, and Plotly to present their findings in an efficient manner. Moreover, the course includes instruction on utilizing SQL for data manipulation, empowering students with the skills needed to make informed decisions based on data.

At the conclusion of the course, you will be fully equipped to utilize these skills in different data analysis situations, establishing a solid groundwork for future studies in data analytics.

This course is designed for:

- Freshers looking to enter the fields of data analysis, data science, or artificial intelligence.

- Individuals with a keen interest in programming who want to enhance their technical skills.

- Professionals seeking to upskill in Python and data manipulation with SQL for practical applications in their careers.

- Anyone curious about data and eager to learn how to analyze and visualize it effectively.

Whether you're starting your tech journey or looking to build a strong foundation, this course will guide you through the essentials of Python and SQL.

You’ll primarily use Python for programming and SQL for data handling, along with visualization libraries and database tools.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.