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SUB-UNIT LEARNING OUTCOMES SESSION/ACTIVITY/PRACTICAL
Identify the AI Project Cycle Session: Introduction to AI Project Cycle
framework. l Problem Scoping l Data Acquisition
l Data Exploration l Modeling
l Evaluation l Deployment
Learn problem scoping and ways to Session: Problem Scoping
set goals for an AI project. Activity: Brainstorm around the theme provided and set a goal for the
AI project.
l Discuss various topics within the given theme and select one.
l Fill in the 4Ws problem canvas and a problem statement to learn
more about the problem identified in the community/ society
l List down/ Draw a mind map of problems related to the selected
topic and choose one problem to be the goal for the project.
Identify stakeholders involved in the Activity: To set actions around the goal.
problem scoped. Brainstorm on the l List down the stakeholders involved in the problem.
ethical issues involved around the
problem selected. l Search on the current actions taken to solve this problem.
l Think around the ethics involved in the goal of your project.
Understand the iterative nature of Activity: Data and Analysis
problem scoping for in the AI project l What are the data features needed?
cycle.
Foresee the kind of data required l How will the features collected affect the problem?
AI PROJECT and the kind of analysis to be done. l Where can you get the data?
CYCLE l How frequent do you have to collect the data?
l What happens if you don’t have enough data?
l What kind of analysis needs to be done?
l How will it be validated?
l How does the analysis inform the action?
Share what the students have Presentation: Presenting the goal, actions and data.
discussed so far. Teamwork Activity:

l Brainstorming solutions for the problem statement.
Identify data requirements and find Session: Data Acquisition
reliable sources to obtain relevant Activity: Introduction to data and its types.
data.
l Students work around the scenarios given to them and think of
ways to acquire data.
Activity: Data Features
l Identifying the possible data features affecting the problem.
Activity: System Maps
l Creating system maps considering data features identified.
To understand the purpose of Data Session: Data Exploration/ Data Visualisation
Visualisation l Need of visualising data
l Ways to visualise data using various types of graphical tools.
Quiz Time
Use various types of graphs to Recommended Activities: Let’s use Graphical Tools
visualise acquired data. l Selecting an appropriate graphical format and presenting the graph
sketched.
l Understanding graphs using https://datavizcatalogue.com/
l Listing of newly learnt data visualization techniques.
l Top 10 Song Prediction: Identify the data features, collect the data
and convert into graphical representation.
l Collect and store data in a spreadsheet and create some graphical
representations to understand the data effectively.