Data Analysis using Python

IBM – Data Analysis Using Python is a comprehensive course that equips learners with essential skills for analyzing data using the Python programming language. Here are the key components covered in this course:

1. Data Analysis Fundamentals:
   • Participants learn the foundational concepts required for effective data analysis.
   • Topics include data cleaning, preparation, and summarization.
2. Python Libraries and Tools:
   • The course delves into using popular Python libraries such as Pandas, NumPy, and SciPy.
   • Learners gain proficiency in working with multi-dimensional arrays, manipulating DataFrames, and performing mathematical routines.
3. Machine Learning with scikit-learn:
   • Participants explore machine learning techniques using the scikit-learn library.
   • They learn how to build and evaluate predictive models.
4. Hands-On Practice:
   • The course emphasizes practical application through Jupyter notebooks in JupyterLab.
   • Learners engage in real-world data analysis tasks, creating meaningful visualizations and predicting future trends.

Whether you’re a data enthusiast, aspiring data scientist, or business professional, this course provides valuable skills for extracting insights from data using Python. 🐍📊

For more details, you can visit the IBM Training page¹.