Foundations of Data Science by Renuka Devi Kailangiri

This beginner-friendly course is designed to introduce learners from all backgrounds to the exciting and rapidly growing field of Data Science. Whether you are a student, professional, or career changer, this course provides a comprehensive overview of what data science is, its interdisciplinary nature, and the career opportunities it offers.

1. Introduction to Data Science

• What is Data Science?

• Importance and impact of data science in today’s world.

• Overview of the data science lifecycle: data collection, cleaning, analysis, and visualization.

2. Interdisciplinary Nature of Data Science

• How data science integrates statistics, mathematics, programming, and domain expertise.

• The role of machine learning, artificial intelligence, and big data technologies.

• Understanding data sources and types: structured vs. unstructured data.

3. Key Roles in Data Science Careers

• Data Scientist: responsibilities and typical tasks.

• Data Analyst: interpreting and visualizing data for decision-making.

• Data Engineer: building and maintaining data infrastructure.

• Machine Learning Engineer: developing predictive models and algorithms.

• Business Analyst and other related roles.

4. Tools and Technologies Overview

• Introduction to popular tools and languages: Python, R, SQL, Tableau, Excel.

• Basics of data manipulation and analysis using these tools.

5. How Data Science Can Reshape Your Career

• Industry demand and future job outlook for data science professionals.

• Transferable skills from data science to other career paths.

• Examples of real-world applications and success stories.

• Tips for transitioning into data science or enhancing your current career with data skills.

6. Course Benefits and Learning Outcomes

• Develop a solid foundational understanding of data science concepts.

• Gain awareness of the diverse career opportunities available in data science.

• Build confidence to pursue further specialized data science courses.

• Understand how to leverage data science knowledge in various industries.