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Python for Data Science with AI

LearnKartS via Coursera

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Details

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

5 weeks, 5 hours a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English, Arabic, Korean, Japanese, Italian, Indonesian, French, Spanish

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Overview

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Step into the world of data science with this course designed to transform beginners into confident, job-ready data analysts. Whether you’re a student, working professional or transitioning careers, this hands-on Python for Data Science with AI course is designed to have you coding right away in Google Colab and solving real-world data challenges with Python from day one. You’ll build a solid foundation in Python programming by mastering variables, data types, control structures, loops, and functions. Then, learn powerful tools like Pandas for cleansing and transforming datasets and Matplotlib & Seaborn for professional visualizations that convey insights. What makes this course stand out? Its case-study-driven approach, pseudocode-first workflow, AI-assisted learning, and heavy hands-on coding ensure you develop the exact practical skills employers are looking for in data roles. By the end, you’ll be able to: • Confidently analyze & clean real-world datasets. • Build data analysis workflows in Python. • Create impactful visualizations & dashboards. • Turn raw data into actionable insights. Ready to launch your data science journey? Enroll now and start analyzing data like a true professional!

Syllabus

Getting Started with Python for Data Science (Beginner Friendly)
- This module introduces you to Python for data science, helping you understand its real-world relevance and setting up your coding environment using Google Colab.You’ll also learn a structured problem-solving approach using pseudocode while working on an initial case study.
Python Basics for Data Analysis: Variables, Data Types & Logic
- This module builds your core Python foundation by covering variables, data types, strings, lists, and control structures like if-else.It also focuses on effective learning strategies and helps you apply these concepts to approach real-world problems confidently.
Python Loops and Functions for Data Processing
- This module teaches you how to use loops and functions to write efficient, reusable, and scalable code.You’ll learn to translate pseudocode into Python programs and apply logic to solve real-world problems.
Data Analysis with Pandas
- This module introduces data analysis using Pandas, where you’ll work with Series and DataFrames to handle real-world datasets.You’ll learn to clean, filter, merge, and analyze data, applying your skills to a practical case study.
Data visualization with Matplotlib and Seaborn
- This module focuses on data visualization using Matplotlib and Seaborn to turn data into meaningful insights.You’ll create and customize a variety of plots and apply the complete workflow to present results effectively.