The IBM Data Science Professional Certification offers a series of 10 course modules aimed at providing essential skills in data science. These courses cover a range of topics, including using open-source tools, programming in Python, database management, analyzing data, creating visualizations, applying statistical methods, and using machine learning algorithms for predictive modeling.
In this repository, there are resources that were needed to complete the certification. Here, you'll find helpful materials such as notes, external sources and urls, some images, code examples that accompany the courses. Additionally, this repository serves as a record of my progress, where you can provide evidence of completing each course successfully.
- ✅ 01. What is Data Science?
- ✅ 02. Tools for Data Science
- ✅ 03. Data Science Methodology
- ✅ 04. Python for Data Science, AI & Development
- ✅ 05. Python Project for Data Science
- ✅ 06. Databases and SQL for Data Science with Python
- ✅ 07. Data Analysis with Python
- ✅ 08. Data Visualization with Python
- ✅ 09. Machine Learning with Python
- ✅ 10. Applied Data Science Capstone
The following key tools out of other tools were predominantly used throughout this certification and please click on image for more details.
The following key Python libraries were used throughout the certification and please click on images for more details.
- Extracting and Visualizing Stock Data
- Chicago Census, Crime, and School Data Analysis using SQL
- House Price Predictions
- Multiple Projects in Course Module 08
- Best Classifier Model
- Predicting Successful Rocket Landings and Interactive web-based app
To verify the certificate, please click on the image below.
