Python for Data Science
Python has become the lingua franca of data science, and this course will make you proficient in using Python for all aspects of data analysis. Learn to manipulate, analyze, and visualize data using the most popular Python libraries in the data science ecosystem.
From data cleaning with pandas to machine learning with scikit-learn, this course covers everything you need to become a Python-powered data analyst. Includes hands-on projects with real-world datasets.
What You'll Learn
Python Fundamentals
Python syntax, data structures, functions, object-oriented programming, and best practices
NumPy for Numerical Computing
Arrays, mathematical operations, broadcasting, and efficient numerical computations
Pandas for Data Manipulation
DataFrames, data cleaning, merging, grouping, time series, and advanced pandas techniques
Data Visualization with Python
Matplotlib, Seaborn, and Plotly for creating compelling visualizations and interactive charts
Statistical Analysis
Using SciPy and statsmodels for statistical testing, distributions, and hypothesis testing
Machine Learning with Scikit-learn
Building and evaluating machine learning models for classification and regression tasks
Your Instructor
Alex Johnson
Python Developer & Data Science Instructor
Alex is a senior Python developer and data scientist with 11 years of experience building data-driven applications. He has contributed to several open-source Python data science libraries and has trained over 10,000 students in Python programming.
His teaching style emphasizes practical coding skills and real-world application, ensuring students can immediately use Python for their analytics projects.
Student Reviews
Perfect course for anyone wanting to use Python for data analysis! Alex explains everything clearly, and the hands-on exercises really helped solidify my understanding.
This course gave me the Python skills I needed to transition into a data analyst role. The projects are practical and mirror real-world scenarios. Highly recommended!