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Expected size of global Data Analytics market by 2030.
Average Salary of a Data Scientist annually.
This course provides a beginner-friendly introduction to Python for data analysis. Learn to work with libraries like Pandas, NumPy, and Matplotlib to clean, manipulate, and visualize data. Explore techniques for performing exploratory data analysis (EDA) and uncovering insights. Designed for aspiring data analysts and professionals, this course equips you with essential skills for making data-driven decisions.
This course teaches you to use Python libraries like Pandas, NumPy, and Matplotlib for data cleaning, manipulation, visualization, and analysis.
It’s ideal for aspiring Data Analysts, Business Analysts, or anyone interested in learning data analysis with Python.
Basic programming knowledge is helpful but not mandatory, as the course introduces Python fundamentals for beginners.
Topics include data manipulation with Pandas, numerical computations with NumPy, data visualization with Matplotlib and Seaborn, EDA, and data cleaning techniques.
Yes, the course includes practical exercises and projects that let you apply your knowledge to real-world datasets.
This course on learning Python for data analysis is 3 hours long.