Data Science & AI Bootcamp

Beginners Class Curriculum

Day 1:

1. Introductions

• Objective: Team Building. Enables Instructor later pair students with strong skills with very early beginners

• Tasks: Each person to talk about themselves and more importantly where the are in technology/Data science

2. Discuss Breakthrough AI products in Health and spaces they are interested in

• Tasks: Get candidates to name AI powered products

3. Understanding Coding and Algorithms

• Objective: Demystify Algorithms

Tasks: Write an algorithm for completing a task in their current field of endeavor. E.g Someone with an Agric background can write an algorithm(steps) for harvesting.

4.Introduction to Programming

1. Variables
2. Assignments
3. Conditions
4. Loops
5. Lists
6. Dictionaries

5. Homework

• Simple Coding Exercises to further demonstrate this skills

Day 2:

6. Introduction to Data Concepts Via Python

• Types / Scale of Data
• File handling
• Functions
• Object Oriented Programming

7. Introduction to Data Analysis

1. The development environments
2. Introduction to libraries and how to use them
3. File handling (revisited)

8. Supervised Class Assignments and Take Home Assignments

   d. List of Topics Based on Perceived areas of most difficult Implementation.

Day 3:

9. Exploratory Data Analysis

a. Numpy 1. Arrays 2. Indexing 3. Selection 4. Slicing 5. Concatenation

b. Pandas 1. Series 2. Dataframes 3. Merging, Joining, Concatenation 4. Data input and Output

C. Visualization using Matplotlib, Seaborn and Pandas Built in Data Viz I. Single plots Ii. Multiplots Iii. Heat Maps e.t.c

Day ⅘:

Project Work and Presentation

Guide Instructions on quick-win techniques

Will be Important at this point to spend some time with the final presenter to aid flawless communication of the work done.

Materials & Resources

1. Instructional Materials:
2. Resources: