This Industry-oriented data science curriculum is designed to equip students with the skills and knowledge needed to apply data science techniques in real-world industry settings. Here are some key components we intend to discuss:

1. Core Data Science Skills:

• Programming: Making students proficient in Python programming.
• Statistics and Probability: Understanding of statistical methods and probability theory.
• Data Manipulation and Analysis: Techniques for cleaning, transforming, and analysing data.
• Data Visualization: Tools and techniques for visualizing data effectively.

1. Soft Skills:
   • Communication: Developing ability to present data insights clearly and effectively.
   • Teamwork: Group assignments.
   • Problem-Solving: Applying critical thinking to solve data-related challenges.

1. Industry Tools and Technologies:
   • Familiarity with tools like Jupyter Notebooks, SQL or MySQL
   • Exposure to cloud platforms like Azure for data storage and processing.

1. Ethics and Legal Considerations:
   • Understanding of data privacy, ethical considerations, and legal compliance in data handling.

For each topic, we will discuss in detail, practise with synthetically made industry data, assignments will be given and feedback will be shared. Test will be conducted. Additional help will be provided to prepare on vendor certification for example, Microsoft Data Scientist DP 100 exam.