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Python for Data Science

This basic of Python for Data Science is an introductory and beginners’ course to learning and understanding the fundamentals of coding in Python, a powerful, modern, industry demanding language. Participants will learn to write programs, perform various operations, manipulate and visualize data. Participants completing this course will be prepared to take up the advanced modules

Duration - 16 Hours |

Learning Format - Online, Interactive

Python for Data Science

Course Description

This beginner-friendly course introduces participants to Python, a powerful and in-demand programming language for data science. Participants will learn fundamental coding concepts, how to manipulate data, access external sources, and visualize insights. By the end of the course, learners will be equipped with foundational Python skills necessary to progress into advanced data science topics.

The course balances theory with hands-on exercises to ensure practical understanding and application of Python in data science

Key Features :

• Understand basic Python syntax and operations

• Use variables, data types, and structures (lists, dictionaries, tuples)

• Write programs using control structures and loops

• Apply Object-Oriented Programming (OOP) concepts

• Read, manipulate, and clean data from files (CSV, Excel, text files)

• Scrape data from the web and access APIs

• Work with Python libraries (NumPy, pandas, matplotlib) for data handling

• Create basic data visualizations (line, bar, scatter plots)

Course Outline:

Introduction to Python & Basic Operations
Control Structures, Loops & OOP Basics
Data Handling & External Data Access
Data Visualization & Python Libraries for Data Science
Final Project & Wrap-Up (Optional)

Skills Covered:

• Python Programming Basics – Writing and running Python scripts

• Logical Thinking & Problem Solving – Using loops, conditions, and functions

• Object-Oriented Programming (OOP) – Creating and using classes and objects

• Data Manipulation – Working with files, lists, and dictionaries

• Web Scraping & APIs – Extracting data from online sources using requests and Beautiful Soup

• Data Visualization – Generating plots and charts using matplotlib

• Working with Python Libraries – Hands-on with NumPy, pandas, and matplotlib

Tools Covered:

Certification: Upon successful completion of the course, participants will receive a certificate showcasing their proficiency in data structures.

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Testimonial

Designers and drafters use it to create two-dimensional (2D) and three-dimensional (3D) computer drawings.

- Vinay Rane

Designers and drafters use it to create two-dimensional (2D) and three-dimensional (3D) computer drawings.

- Sandeep Singh

Designers and drafters use it to create two-dimensional (2D) and three-dimensional (3D) computer drawings.

- Sonal Singh

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