The IBM Data Science Professional Certificate consists of 12 courses designed to equip you with the necessary tools and skills to excel in data science. The curriculum covers open-source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning.

• 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
• 11. Generative AI: Elevate Your Data Science Career
• 12.Data Scientist Career Guide and Interview Preparation

The following tools were utilized to complete the certification:

P.S. More information can be obtained by clicking on the corresponding icon.

Throughout the certification, the following Python libraries were employed:

P.S. More information can be obtained by clicking on the corresponding icon.

• Programming Language Statistics in The Class

• [Extracting and Visualizing Stock Data](https://github.com/adam951502/IBM_Data ::contentReference[oaicite:1]{index=1}

• Extracting and Visualizing Stock Data

If you encounter an error related to filename length while cloning this repository on Windows, follow these steps to enable long path support:

1. Open PowerShell as Administrator.
2. Run the following command:

   git config --system core.longpaths true

3. Try cloning again:

   git clone https://github.com/adam951502/IBM-Data-Science-Professional-Certificate.git

1. Press Win + R, type regedit, and press Enter.
2. Navigate to:

   HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\FileSystem
   

3. Find LongPathsEnabled and double-click it.
4. Change the value from 0 to 1.
5. Restart your computer.
6. Try cloning again.

If the issue persists, you can clone without checking out problematic files:

git clone --no-checkout https://github.com/adam951502/IBM-Data-Science-Professional-Certificate.git
cd IBM-Data-Science-Professional-Certificate
git sparse-checkout init
git sparse-checkout set "<folder-you-need>"
git checkout

This avoids checking out long filenames.