Hi there! This repository documents my learning journey through the IBM course "What is Data Science?" — the first course in the IBM Data Science Professional Certificate specialization. This course served as my introduction to the world of data science, and through it, I explored its impact, career opportunities, and foundational concepts like big data, machine learning, and artificial intelligence.
Below is a summary table of the modules I completed in the course:
| Module No. | Module Title | Key Topics Covered | What I Learned |
|---|---|---|---|
| Module 1 | Introduction to Data Science | - What is Data Science? - Role of a Data Scientist - Skills, file types, and big data |
I understood the fundamentals of data science and what a data scientist does |
| Module 2 | AI & Big Data in Transformation | - Big Data + Cloud - Data Mining - AI, Machine Learning, Deep Learning |
I learned how AI, ML, and cloud computing work together to drive digital transformation |
| Module 3 | Applications of Data Science | - Business, healthcare, finance, and marketing use cases - Hands-on data science activities |
I explored real-world applications of data science across industries |
| Module 4 | (Optional) Data Literacy for Data Science | - Data Ecosystem - ETL Process - Databases, Warehouses, Lakes - Pipelines |
I gained foundational knowledge in data infrastructure and data movement processes |
I enrolled in this course to:
- Understand what data science is and why it's in such high demand
- Learn about different career paths in data science
- Hear directly from data scientists about their experiences
- Begin building the foundational skills for a career in this field
By taking this course, I learned:
- What a data scientist does and what skills are essential
- How big data, artificial intelligence (AI), machine learning (ML), and deep learning are applied in real life
- How data science helps organizations tell compelling stories and make informed decisions
- Why data science has been called “the sexiest job of the 21st century”
- Instructional videos and guided lessons
- Industry interviews with practicing data scientists
- Readings and interactive glossaries
- Practice assessments and summary videos
- A final case study and a peer-reviewed job market project
This course was ideal for me because:
- I had no prior experience in data science or programming
- I was curious about how data science works and what it takes to get started
- I wanted to transition into a more data-oriented role or start a career in data
Completing this course was the first step in my data science journey. I now plan to continue with:
- The full IBM Data Science Professional Certificate specialization
- Courses in Python, data analysis, and machine learning
- Projects that apply what I’ve learned to real-world datasets
After finishing this course, I:
- Earned a certificate of completion
- Built a solid understanding of foundational data science concepts
- Am ready to explore job opportunities in data science with more clarity and confidence
- Have a clear path forward to deepen my technical skills
I’m excited to continue this learning path and grow into a data science professional. Thanks for checking out my notes and progress from the IBM "What is Data Science?" course!
