Python for Data Science Workshop
Project Overview
This intensive 3-day workshop, held at Qazvin Azad University, offered a comprehensive, hands-on journey into the world of Data Analysis and Machine Learning with Python. The program was carefully structured to build knowledge from the ground up, beginning with a solid foundation in core Python programming concepts and syntax.
Once participants mastered the fundamentals, we transitioned to setting up a professional development environment using essential tools like Conda, Shell, and Jupyter Notebooks. From there, the curriculum delved deep into data manipulation and analysis with Pandas and NumPy. The final phase focused on applying this knowledge to real-world challenges, covering data visualization with Matplotlib and Seaborn, and introducing machine learning principles using industry-leading libraries such as Scikit-learn and PyTorch.
Key Features
- Foundations-First Approach: The workshop started with core Python syntax and programming logic to ensure all participants had a strong base.
- Intensive 3-Day Program: A focused and immersive learning experience covering the complete data science pipeline.
- Hands-On Practical Training: Emphasis on practical skills, moving from environment configuration to solving complex data problems.
- Comprehensive Curriculum: A complete journey from Python fundamentals to advanced data analysis and machine learning applications.
- Industry-Standard Tooling: In-depth training on a wide array of essential libraries for data science, visualization, and machine learning.
- Project-Based Learning: Designed to empower participants with the confidence and skills to immediately tackle their own data science projects.
Technology Stack
- Core & Environment:
- Python
- Conda
- Shell (Bash)
- Jupyter Notebook / JupyterLab
- Data Analysis & Scientific Computing:
- NumPy
- Pandas
- SciPy
- Database:
- Matplotlib
- Seaborn
- Plotly
- Machine Learning & Deep Learning:
- Scikit-learn
- PyTorch
- Keras