Micro-Credential in Quantitative Methods

1. Asynchronous 1 - Topics
   Math review, The Normal Distribution, Algebra of Random Variables, The Normal CDF
2. Class 1 - Topics
   Activity: Competing with Probability Distributions,
   Activity: Understanding Histograms, The Inverse Normal CDF,
   Activity: Finding the Limits of The Central Limit Theorem
3. Asynchronous 2 - Topics
   Hypothesis testing, The T-Distribution, Difference-in-means-tests, Using Google Colab
4. Class 2 - Topics
   Hypothesis Testing Projects: Choosing Thresholds for Fraud Detection, Avoiding False Positives in A/B Testing
5. Asynchronous 3 - Topics
   One-tailed tests, Confidence Intervals, Bootstrapping, Using AI for Analytics
6. Class 3 - Topics
   Activities: Data Viz and Analytics with AI
7. Asynchronous 4 - Topics
   More Algebra for Random Variables , Correlation and Covariance, The Binomial Distribution
8. Class 4 - Topics
   Activity: More AI Analytics, Project: Correlation and Product Bundling
9. Asynchronous 5 - Topics
   Dimensionality Reduction
10. Class 5 - Topics
    Project: Making Big Data Manageable with Dimensionality Reduction

At the end of the course, you will be able to:

• Solve foundational mathematical problems in topics like probability and statistics, using both classic spreadsheets and AI tools
• Apply statistical techniques and quantitative analysis to business problems management.
• Propose rational decisions in a variety of business contexts.

Anyone without a background in analytics but wants to develop their skills and knowledge in analytics.

Quantitative Preparation course (for those with limited background in Math). Please note that a link to this course will be shared to ACE learners upon registration.