Programming

Introduction to Data Science

This beginner-level course introduces Class 8 students to the fascinating world of data science, focusing on hands-on learning and real-world applications. Students will explore how data impacts their everyday lives, learn to collect, organize, analyze, and visualize data, and gain basic programming skills using Python.

  • 4/5.0
  • 100 Students
  • Beginner
  • English
Course Description

This beginner-level course introduces Class 8 students to the fascinating world of data science, focusing on hands-on learning and real-world applications. Students will explore how data impacts their everyday lives, learn to collect, organize, analyze, and visualize data, and gain basic programming skills using Python.

What you’ll learn
  • Comprehensive Learning Path: Step-by-step guide to mastering topics.
  • Interactive Learning: Engage with quizzes, discussions, and activities.
  • Skill Development: Improve technical and soft skills.
  • Flexible Learning: Learn at your own pace.
  • Career Advancement: Equip yourself for job market success.
  • Networking Opportunities: Connect with professionals and experts.
  • Practical Tools and Resources: Access industry-standard tools and resources.
  • Ongoing Support: Get continuous feedback and assistance.
  • Hands-On Projects: Complete real-world projects and tasks.
  • Final Certification: Earn a recognized course certification.

Each course is designed with the highest quality standards to ensure you gain valuable knowledge and practical skills. Whether you're exploring new areas or deepening your expertise, our courses offer a comprehensive learning experience. With detailed explanations, real-world examples, and expert guidance, you'll be equipped to apply what you've learned immediately. Join us and unlock new opportunities for growth and success

Introduction to Data Science: Why it’s important.


Real-Life Applications of Data Science (e.g., sports, entertainment, health).


The Data Science Workflow: Collect, Clean, Analyze, Visualize, Interpret.


What is Data? Types of Data: Quantitative and Qualitative.


Sources of Data: Surveys, Sensors, Social Media.


Introduction to Datasets: Rows, Columns, and Data Points.


Basics of Python for Data Science


Writing Simple Python Code: Variables, Loops, and Conditionals.


Introduction to Python Libraries: Pandas, Matplotlib, and Seaborn.


How to Collect Data: Surveys, Online Sources, and Experiments


Cleaning Data: Identifying Missing or Incorrect Data.


Organizing Data in Tables Using Python.


Importance of Data Visualization: Telling Stories with Data.


Types of Visualizations: Bar Graphs, Line Charts, Pie Charts, and Histograms.


Creating Visualizations Using Matplotlib and Seaborn in Python.


Descriptive Statistics: Mean, Median, Mode, and Range.


Finding Patterns and Trends in Data.


Basics of Correlation and Relationships Between Variables.


Understanding Data Ethics: Why it Matters.


Data Privacy: How Companies Use Data and Protect It.


Identifying and Avoiding Bias in Data.


Objective


Example Projects


Presenting the Project


instructor-image

Anjali Gupta

About Instructor

Inspiring Learning, One Step at a Time As an educator, your dedication transforms students' lives. Our platform is designed to empower you with tools, resources, and a community that values your expertise. Share your knowledge, inspire curiosity, and help learners achieve their dreams. Together, we build a brighter future, one lesson at a time.

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This course includes

  • Lectures 20 Classes
  • Duration Hours
  • Skills Beginner
  • Language English
  • Certificate Yes