Course Overview
- Course Title: Data Analysis with Pandas & NumPy
- Instructor: Muhammad Shafiq (Data Scientist | AI & ML Engineer | Lecturer | Researcher)
- Target Audience:
- Beginners in data analysis or Python programming
- Developers transitioning into data science or machine learning
- Professionals seeking to enhance data manipulation skills
- Prerequisites:
- Basic understanding of Python syntax
- Familiarity with programming concepts (e.g., loops, functions)
Curriculum Highlights
- Key Topics Covered:
- NumPy fundamentals (arrays, indexing, operations)
- Pandas DataFrames & Series (creation, manipulation)
- Data cleaning (handling missing values, duplicates)
- Data transformation (aggregation, grouping, pivoting)
- Advanced indexing & merging datasets
- Basic data visualization (using Pandas & Matplotlib)
- Real-world dataset projects
- Key Skills Learned:
- Efficient data loading & preprocessing with Pandas
- Numerical computations using NumPy
- Data wrangling for structured datasets
- Exploratory data analysis (EDA) techniques
- Preparing data for statistical analysis or machine learning
Course Format
- Duration: N/A (Self-paced; includes 3 practice tests)
- Format: Online, self-paced (video lectures, hands-on exercises)
- Resources:
- Mobile access (learn on-the-go)
- Practice tests for skill reinforcement
- Downloadable code samples & datasets