The program curriculum caters to the 2nd, 3rd, and 4th year students from the partner engineering colleges as summarised below:
Content Type |
Duration (Hours) |
Delivery Type |
Delivery Mode |
2nd Year |
3rd Year |
4th Year |
1 |
Core Deep Tech Offering |
~40 |
~55 |
~20 |
Instructor led |
Hybrid |
2 |
Industry Specific Modular Offering |
~10 |
~15 |
~20 |
Instructor led |
Hybrid |
3 |
Employability Skills |
- |
~15 |
~15 |
Instructor led |
Hybrid |
4 |
Capstone Project |
~20 |
~30 |
~60 |
Instructor led |
Hybrid |
Year-wise Total Hours |
70 |
115 |
115 |
|
|
The core technical content breakdown has been delineated below:
II Year - Foundation Course
Overview of Foundation Course:
The Foundation Course under Code Unnati Program will be offered to the second and pre-final students pursuing engineering and other technical degree courses. This course will cover the pre-requisites required for Artificial Intelligence, Machine Learning, Data Analytics, Deep Learnings, Computer Vision Technologies of the Code Unnati Advance and Value-Added Course for the pre-final/final year students.
Learning Outcomes:
- Demonstrate fundamentals of Python tools and its data analytics libraries.
- Able to generate visualizations using Python.
- Understand the concept and applications AI.
- Understanding industry-specific SAP tool.
Foundation Course Outline (50 Hours)
- Introduction to Python Programming
- Python setup – Getting Started with Python
- Python Object and Data Structure
- Python Comparison Operator
- Python Conditional Statements
- Python OOPS Concept
- Python Functions & Methods
- Data Science vs Data Analysis vs Data Analytics
- Working with Python for Data Science
- Python packages for Data Analytics Applications
- NumPy
- Matplotlib
- Pandas
- Seaborn
- Data Analysis Use Cases
- Introduction to AI and Understanding different AI Terminologies
- Understanding the Evolution of AI and the AI Winter Cycle
- AI Applications Transforming Various Industries
- Current AI Market Trends and Opportunities
- SAP – Overview, various services offered by SAP, SAP products
- SAP AI conversational Chatbot Application – Hand on
- Introduction to Chatbot
- Deployment of Chatbot to Third Party Application
- Capstone Project is based on learning and students create prototype level solution for real life problems.
- Design Thinking – way to solve problems with creative thinking.
Machine Learning, Computer Vision, IoT, SAP Tech. Skills 5 Days Workshop
Workshop Objective/Outcome:
- To bridge the industry-academic gap by preaching the latest technology trends
- Exposure to different concepts, tools and algorithms in building intelligent systems through experiential learning
- Learn how to use Python libraries to develop Machine learning applications
- Use data analytics tools and technologies with ease
- Translate data-driven insights into decisions and actions.
- Equip themselves with knowledge in areas of Data Analytics, AI, ML and computer vision, Deep Learning
- Develop the SAP tech level skills to deploy applications based of SAP tools ABAP & Analytic Cloud
Workshop Prerequisite:
- Prior knowledge of basic python and its packages like NumPy, Pandas, and scikit-learn would be an advantage
- Working experience of Python Programming tools and IDE like Anaconda and Jupyter notebook
- Prior basic knowledge of Linux commands and familiar with Linux environment
Tools/Software requirements:
- Laptop/Computer with minimum i3 processor, 4GB RAM running with 64-bit Windows 10 or above along with access of internet connection with adequate speed.
- Anaconda for with python 3
NOTE: *Uninterrupted high-speed LAN and Wi-Fi connectivity without any proxy is necessary for the training program
Workshop Agenda:
Sl. No.
|
Topic Description
|
Duration (30 Hrs.)
|
FDP Pre-assessment
|
Day-1
|
1.
|
Introduction – Workshop Agenda, Objective
Data Analytics with Python
· Numerical Python - NumPy
· Pandas (Data Manipulation and data analysis)
· Data Visualization Using Matplotlib and Seaborn
Machine Learning Algorithms
· Introduction – Machine Learning – Supervised, unsupervised ML
· Linear Machine learning model (linear regression/ logistic regression and it's Evaluation matrices).
|
6Hrs
|
Day-2
|
2.
|
Machine Learning Algorithms
· Ensemble Machine learning models
· Dimensionality Reduction Techniques (PCA)
· Non-Linear Model (SVM & KNN)
|
6Hrs
|
3.
|
Deep Learning
· Neural Networks – Neurons, Loss Functions, Weights
· Gradient Descent and Back propagation
· Convolutional Neural Network
· Computer Vision – With Open cv and Keras
|
Day-3
|
4.
|
Hands-on session on Computer vision
· Canny edge detection
· Viola-Jones Algorithm for face detection
· Face detection
· Full body detection
· Number plate detection
|
6Hrs
|
5.
|
IoT Fundamentals
· Internet Usage and Population Statistics.
· IoT in Technical Perspective.
· Introduction to Raspberry Pi 4B.
· Installation of operating system on Raspberry PI
|
Day-4
|
6.
|
Hands on with Raspberry pi and DFRobot
· Hardware connection for DFRobot
· Sensors and Actuators
· LED interfacing with Raspberry PI
· Light Sensor interfacing with Raspberry PI
· Automatic streetlight
· Button interfacing with Raspberry PI
· Ultrasonic Sensor interfacing with Raspberry PI
SAP Tech Skills
SAP Business Technology Platform ABAP Environment
· Understanding the SAP BTP platform
· Creating a BTP ABAP Environment
· Creating an ABAP Package
|
6Hrs
|
Day-5
|
7.
|
ABAP RESTful Programming Model
· Condition statement and looping with ABAP
· Creating a Database Table
· Create an ABAP Class
· Conditional statement and looping with sap ABAP
· Introduction of ABAP RESTful Application Programming Model
· Developing a Read-Only List Report App
· Enabling the Transactional Behavior of an App
· Dealing with Existing Code
SAP Analytics Cloud
· Getting Started with Stories
· Building Stories
· Configuring Story Elements
· Manipulating Data in Stories
· Presenting Stories
|
6Hrs
|
|
FDP Post assessment and Feedback
|
|