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Students will be able to: The Global Demand Identify ten companies
currently hiring employees for
Articulate the demand for AI Some Common Job Roles In AI Note down the technical skills
in specific AI positions.
professionals and the diverse career
UNLOCKING YOUR FUTURE IN AI Understand the potential roles and Opportunities in AI across companies for the specific AI
Essential Skills and Tools for
opportunities available in the field.
Prospective AI Careers
and soft skills listed by any two
Identify the requisite skills and tools
needed to pursue a career in artificial
Various Industries
position.
intelligence.
IBM Skills Build : Your Future in
AI: The Job Landscape
responsibilities of AI professionals
across different industries.
Explore resources for further learning
and skill development in the field of
AI.
Evaluate their own interests and skills
to determine potential pathways for a
career in AI.
Students will be able to: Level 1 : Basics of python Minimum five programs to be
Explain the basics of python programming, character taught using operators, data
sets, tokens, modes,
types, control statements (Level
programming language and write
PYTHON PROGRAMMING Use selective and iterative statements Level 2 : CSV Files, Libraries – Minimum 5 programs on
1)
operators, datatypes,
programs with basic concepts of
Control Statements
tokens.
Numpy, Pandas, Scikit- learn
Numpy, Pandas, Scikit-
(Level 2)
effectively.
learn
IBM SkillsBuild - Python for
Gains practical knowledge on how to
Data Science
use the libraries efficiently.
INTRODUCTION TO CAPSTONE PROJECT Students will be able to: Design Thinking Create an empathy map for a
given scenario
Decompose any problem using the
Empathy Map
Project Abstract Creation Using
5W1H method.
Sustainable Development Goals
Design Thinking Framework
Apply Design thinking methodology.
Capstone Project
IBM SkillsBuild - What is
Create empathy maps.
Design thinking?
Align problems to SDGs.
Apply all the learnings in solving real
world problems.
Comfortably express their solution to
a problem in non-technical words.
DATA LITERACY – DATA COLLECTION TO DATA ANALYSIS Students will be able to: What is Data Literacy? Identification of the level of
measurement
Data Collection
Explain the importance of data literacy
to
Python
programs
in AI.
Exploring Data
demonstrate the use of mean,
Identify different data collection
Statistical Analysis of data
standard
mode,
median,
methods and their applications.
deviation and variance
Representation of data, Python
Comprehend mathematical concepts
Programs for Statistical Analysis
Python programs to visualise
related to matrices, its operations, and
and Data Visualisation
the line graph, bar graph,
applications.
histogram, scatter graph and
Introduction to Matrices
Apply basic data analysis techniques
pie chart using matplotlib
Data Pre-processing
to analyse data.
IBM SkillsBuild - Data Visualisation
Data in Modelling and Evaluation
Visualize the data using different
with Python (Modules 1,2,3)
techniques.

