LEARNING OUTCOMES

• Learning python structure and how to write programs in it
• Basic concepts of Python, its syntax, functions, and conditional statements
• Acquire the prerequisite Python skills to move into specific branches – Machine Learning, and Data Science
• Understand packages to enable them to write scripts for data manipulation and analysis

LEARNING OUTCOMES

• Introduce statistical tools for working with datasets
• Learn the essentials of probability and statistics for data analysis & visualization
• Know how to import and clean data using libraries like NumPy and Pandas for data exploration and analysis
• Learning to fix incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset

LEARNING OUTCOMES

• Acquire a fundamental understanding of the analytical techniques and software tools necessary to effectively generate useful information from structured and unstructured datasets of any size CHARTS
• Gain experience in using the tools and techniques of data science to structure and complete projects focused on obtaining actionable insights from complex data
• Dive deeply into a chosen area of practice to fully prepare to use the knowledge gained in the program to add significant value in a professional setting
• Be able to utilize knowledge and skills to continue learning and adapting to new data science technologies

LEARNING OUTCOMES

• Power BI’s Data, Model, and Report views
• learn how to change and format a wide range of visualizations, before moving on to sorting data and creating hierarchies—making it possible for you to drill into your reports
• learn how to shape and transform your data before the data analysis using Power Query Editor
• How to filter the information in your reports by location and control how these filters interconnect and interact with other visuals in your report