Introduction to “Data Science” with Python
What is Data Science?
- Data Science involves extracting valuable information from data to make predictions and decisions.
- Its importance is paramount in our data-driven society.
Why Use Python?
- Python is currently the most popular programming language for data science.
- Its versatility and ease of use make it widely adopted among data scientists and analysts.
- Python’s powerful library ecosystem simplifies data processing and analysis tasks.
Learning Objectives
- Data Collection and Preprocessing: Acquire methods for collecting, cleaning, and transforming data
- Data Visualization: Visualize and present analytical results using libraries like Matplotlib and Seaborn
- Building and Evaluating Machine Learning Models: Utilize frameworks such as Scikit-learn, TensorFlow, and PyTorch to build and evaluate models
- Statistical Analysis: Develop statistical analysis skills using SciPy
Target Audience
- Open to anyone (no prerequisites required)
- This course is designed for beginners, starting with basic Python syntax and progressing to more advanced libraries.
Requirements
- Students: Personal laptop
- Institution: Classroom with internet, HDMI, and projector
- All additional resources needed (account setups, power strips, etc.) will be provided and prepared by AI Castle.
Example Exercises
- Python Syntax
- Numerical Computation
- Data Handling
- Visualization
Curriculum
- This course is optimized for 48 hours of instruction.
- A minimum of 40 hours and up to 60 hours is recommended.