Data Science for Executives

Data Science for Executives

2-Days

If you work in human services because you hate math, terms like “data,” “quantitative analysis,” or “pivot table” might sound scary. Don’t be intimidated! Data does not have to be complicated. Simply stated, data is useful information that you collect to support organizational decision-making and strategy.

This two day course is designed to get you a solid understanding of what each of the terms such as “Big Data”, “AI”, “Machine Learning” and other terminologies means and how it can help you by understanding its workings. You will not have to master mathematics or know programming to be able to grasp how they work or how they can help your business.

Learning Outcome

Although everyone has different learning curves, this course will attempt to equip the learner with the following set of abilities:

• Genuinely understand what
  • Computer Science,
  • Algorithms,
  • Programming,
  • Data,
  • Big Data,
  • Artificial Intelligence,
  • Machine Learning, and
  • Data Science is.
• Have a working understanding of how the Machine Learning Process works.
• Know what problems Machine Learning can solve.
• How data impacts the world today.
• What skills to look for when implementing any of the above mentioned technology.
• Understand the technical requirements for implementing any of the technologies mentioned above.
• Explore use cases of how the implementation of similar technology helped businesses.

Prerequisite

• PC / Laptop
• Webcam
• Stable internet connection
• Basic understanding of how the internet works.

Course Outline

This two day course will be covered from the ground up. The contents of the course are as follows:

1. Introduction
   1. Core Concepts
   2. Computer Science - the ‘Informal' exploration
   3. Data - an unorthodox approach
   4. Structured vs Unstructured Data
   5. Structured and Unstructured Data
   6. Computer Science - Definition Revisited & The Greatest "lie" ever SOLD....
   7. What's big data?
   8. What is Artificial Intelligence (AI)
   9. What is Machine Learning?
   10. Exploration of ML
   11. What is data science?
   12. Recap & How do these relate to each other?
2. Discovery
   1. Impacts, Importance and examples - Overview
   2. Why is this important now?
   3. Computers exploding! - The explosive growth of computer power explained.
   4. What problems does Machine Learning Solve?
   5. Where it's transforming our lives
3. Machine Learning
   1. The Process Overview
   2. 5 Step Machine Learning Process
   3. How it matters
   4. How to apply Machine Learning for Data Science
   5. Where to begin your journey
   6. Common platforms and tools for Data Science
   7. Case study
4. Big Data
   1. Why Big Data?
   2. Tools of the trade
   3. Implementation
   4. Challenges
   5. Comparative analysis
   6. Cost factor
   7. What to look for when choosing to utilize Big Data
5. Conclusion
   1. Discussion
   2. Q/A