IBM Data Science Professional Certificate

Overview

This repository contains the assignments and project files completed as part of the IBM Data Science Professional Certificate offered through Coursera. This certification programme, developed by IBM, is designed to prepare learners for a career in data science by equipping them with job-ready and AI-driven skills. The programme does not require any prior experience in programming or computer science.

Certificate Details

• Provider: IBM via Coursera
• Instructors: IBM Skills Network Team, Dr. Pooja, Abhishek Gagneja
• Level: Beginner
• Duration: Approx. 4 months (10 hours/week)
• Language: English
• Delivery Mode: Online, self-paced
• Credential: IBM Professional Certificate

What You'll Learn

• Master current data science tools and libraries including Python, SQL, Pandas, NumPy, Scikit-learn, Matplotlib, and more.
• Import, clean, analyse and visualise data.
• Build machine learning models and data pipelines.
• Develop a portfolio of projects to showcase your data science skills.
• Work with Jupyter, GitHub, Watson Studio, and other industry-standard tools.

Skills Gained

• Data Literacy
• Interactive Data Visualisation
• Exploratory Data Analysis (EDA)
• Feature Engineering
• Unsupervised Learning
• Generative AI
• Dashboard Creation
• SQL & Databases
• Statistical Modelling

Course Breakdown

This programme comprises 12 individual courses:

1. What is Data Science? – 11 hours
2. Tools for Data Science – 18 hours
3. Data Science Methodology – 6 hours
4. Python for Data Science, AI & Development – 25 hours
5. Python Project for Data Science – 8 hours
6. Databases and SQL for Data Science with Python – 18 hours
7. Data Analysis with Python – 15 hours
8. Data Visualisation with Python – 20 hours
9. Machine Learning with Python – 20 hours
10. Applied Data Science Capstone – 13 hours
11. Generative AI: Elevate Your Data Science Career – 13 hours
12. Data Scientist Career Guide and Interview Preparation – 9 hours

Applied Learning Projects

Key Projects:

• Extract and graph financial data using Pandas
• Perform SQL queries on census and crime data sets
• Visualise and predict housing prices using regression models
• Create an interactive dashboard for flight reliability
• Predict loan case outcomes with classification algorithms

Repository Structure

IBM-Data-Science-Specialization/
│
├── Tools for Data Science/
├── Python Project for Data Science/
├── Data Analysis with Python/
└── Applied Data Science Capstone/

Each directory contains the relevant notebooks and files used to complete the course-specific assignments and projects.

Acknowledgements

• Special thanks to the IBM Skills Network Team and Coursera for delivering a comprehensive learning experience.
• Course link: IBM Data Science Professional Certificate on Coursera

Author

Debarjun Chakraborty
GitHub: DebarjunChakraborty