Digital Start-Up for IT Professional (DSU-ITP)

Overview: 

Part 1 

Day 

Program Topics 

Learning Hours 

1 

Data Science & Machine Learning 

  • Applied Data Science with Python and Jupyter 

8 hours 

2 

Cloud Computing  

  • Azure Fundamentals 

8 hours 

3 – 7 

Cloud Computing  

  • Analyzing Data with Microsoft Power BI 

32 hours 

8 

Lean Start-up (Accelerator – IDEATION) 

8 hours 

9 

Lean Start-up (Accelerator – CONCEPTION) 

8 hours 

10 

Growth Hack 

8 hours 

 

Part 2 

Day 

Program Topics 

Learning Hours 

11 

Design Thinking & Problem Solving 

8 hours 

12 

Effective Workplace Communication 

8 hours 

 

Programme Outlines

APPLIED DATA SCIENCE WITH PYTHON AND JUPYTER 

 

Overview: 

Data science is becoming increasingly popular. Python is a popular choice for most data scientists, owing to its ease of use and versatile nature. In this course, we show how Jupyter Notebooks can be used with Python for various data-science applications. Aside from being an ideal "virtual playground" for data exploration, Jupyter Notebooks are equally suitable for creating reproducible data processing pipelines, visualizations, and prediction models. 

 

Outcome: 

This course focuses on creating reproducible data analyses using Python and Jupyter, and is intended for an audience with a background in Python. As such, we do not cover the basics of Python in this course. However, we will take a brief tour of the Jupyter interface. 

 

Outline: 

  • Lesson 1: Jupyter Fundamentals 
  • Lesson 2: Data Cleaning and Advanced Machine Learning  
  • Lesson 3: Web Scraping and Interactive Visualizations 

Course Detail

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