1. IBM Data Science ✅
2. IBM Data Analyst ✅
3. IBM Data Engineer ✅
4. IBM Data Warehouse ✅
5. IBM NoSQL & Big Data ✅
6. IBM DevOps ⏳ (see progress below)
7. IBM Full-Stack Cloud Native ⏳ (see progress below)

1. Data Warehouse ✅
   1. Introduction to Data Engineering [91.20%]
   2. Introduction to Relational Databases (RDBMS) [91.70%]
   3. Databases and SQL for Data Science with Python [98.84%]
   4. Hands-on Introduction to Linux Commands and Shell Scripting [94%]
   5. Relational Database Administration (DBA) [95.80%]
   6. ETL and Data Pipelines with Shell, Airflow and Kafka [94%]
   7. Getting Started with Data Warehousing and BI Analytics [94%]
2. NoSQL, Big Data and Spark ✅
   1. Introduction to NoSQL Databases [94%]
   2. Introduction to Big Data with Spark and Hadoop [94.3%]
   3. Data Engineering and Machine Learning using Spark [100%]
3. Data Engineering ✅
   1. Introduction to Data Engineering [91.20%]
   2. Python for Data Science, AI & Development [94.60%]
   3. Python Project for Data Engineering [100%]
   4. Introduction to Relational Databases (RDBMS) [91.70%]
   5. Databases and SQL for Data Science with Python [98.84%]
   6. Hands-on Introduction to Linux Commands and Shell Scripting [94%]
   7. Relational Database Administration (DBA) [95.80%]
   8. ETL and Data Pipelines with Shell, Airflow and Kafka [94%]
   9. Getting Started with Data Warehousing and BI Analytics [94%]
   10. Introduction to NoSQL Databases [94%]
   11. Introduction to Big Data with Spark and Hadoop [94.3%]
   12. Data Engineering and Machine Learning using Spark [100%]
   13. Data Engineering Capstone Project [99%]
4. Data Science ✅
   1. What is Data Science? [97.50%]
   2. Tools for Data Science [97.91%]
   3. Data Science Methodology [96.50%]
   4. Python for Data Science, AI & Development [94.60%]
   5. Python Project for Data Science [100%]
   6. Databases and SQL for Data Science with Python [98.84%]
   7. Data Analysis with Python [97%]
   8. Data Visualization with Python [97.91%]
   9. Machine Learning with Python [95%]
   10. Applied Data Science Capstone [97%]
5. Data Analyst ✅
   1. Introduction to Data Analytics [86%]
   2. Excel Basics for Data Analysis [100%]
   3. Data Visualization and Dashboards with Excel and Cognos [97%]
   4. Python for Data Science, AI & Development [94.60%]
   5. Databases and SQL for Data Science with Python [98.84%]
   6. Python Project for Data Science [100%]
   7. Data Analysis with Python [97%]
   8. Data Visualization with Python [97.91%]
   9. IBM Data Analyst Capstone Project [89%]
6. DevOps and Software Engineering ⏳
   1. Introduction to DevOps [98.5%]
   2. Introduction to Cloud Computing [100%]
   3. Introduction to Agile Development and Scrum [96%]
   4. Hands-on Introduction to Linux Commands and Shell Scripting [94%]
   5. Getting Started with Git and GitHub [100%]
   6. Python for Data Science, AI & Development [94.60%]
   7. Introduction to Containers with Docker, Kubernetes and OpenShift [96.84%]
7. Full-Stack Cloud Native Software Developer ⏳
   1. Introduction to Cloud Computing [100%]
   2. Getting Started with Git and GitHub [100%]
   3. Introduction to Containers with Docker, Kubernetes and OpenShift [96.84%]
   4. Python for Data Science, AI & Development [94.60%]
8. Data Visualization and Communication with Tableau [85.98%] ✅

Some Courses are appeared in more than one learning path.