Robotic Agentic Automation

Course Code: CA212E

Course Name: Robotic Agentic Automation

L

T

P

C

 

3

0

0

3

Pre-requisite: Basic understanding of any programming language (preferably Python), along with fundamental computer and logical problem-solving skills.

Course Objectives:

This course provides a comprehensive understanding of Generative AI, LLMs, and RAG architectures for modern intelligent systems, while equipping students to design and deploy agentic AI solutions in real-world contexts. It also develops practical competency in RPA using UiPath, enabling automation of business workflows, alongside hands-on skills in data handling, UI automation, and integrating AI with automation tools for industry-ready applications.

Course Outcome:

Students will be able to:

BL

KC

CO1

Understand concepts of Generative AI, LLMs, prompt engineering, and RAG architecture for building intelligent systems.

2

C

CO2

Demonstrate agentic AI principles and multi-agent systems by integrating RAG with real-time applications.

3

P

CO3

Illustrate UiPath components, variables, arguments, and control flows to develop structured automation workflows.

3

P

CO4

Apply data manipulation, Excel automation, and UI automation using selectors and activities in UiPath.

3

P

CO5

Apply advanced automation techniques including debugging, exception handling, and RE Framework to build robust enterprise-level automation solutions.

3

P

 

CO-PO Mapping (Scale 1: Low, 2: Medium, 3: High):

CO-PO Mapping

PO1

PO2

PO3

PO4

PO5

PO6

PO7

PO8

CO1

2

2

1

2

1

-

-

2

CO2

2

2

2

2

2

-

-

2

CO3

2

2

3

2

2

1

-

2

CO4

2

2

3

2

2

1

-

2

CO5

2

2

3

2

3

2

1

2

 

Detailed Syllabus

Unit 1

LLMs & RAG Foundations

08 hours

Introduction to Generative AI & LLMs, Prompt Engineering techniques, RAG pipeline & architecture, Vector databases (FAISS, Pinecone)

Hands-on: Chat with PDFs

Unit 2

 Agentic AI Systems

08 hours

Agent architecture (LLM, Tools, Memory), React framework (Plan → Execute → Observe), Multi-agent systems, RAG + Agent integration, Real-time voice agents

Hands-on:

1. Creating a simple AI agent with LLM, tools, and memory

2. Implementing Plan → Execute → Observe flow for task completion

3. Building a basic multi-agent or RAG-integrated agent workflow

4. Case Study: Developing a simple real-time chat or voice-based agent application

Unit 3

UiPath Studio Basics

08 hours

UiPath components: Studio, Robot, Orchestrator, Variables & Arguments, Control Flow (If, Switch, Loops), Hands-on workflows

Hands-on:

1. Creating a basic automation workflow in UiPath Studio

2. Using variables and arguments to pass data between activities

3. Implementing control flow using If, Switch, and Loops in automation tasks

4. Case Study: Building a simple business process automation workflow using UiPath Robot and Orchestrator

Unit 4

Data Manipulation & UI Automation

08 hours

Data Tables & Excel automation, UI Activities (Click, Type Into), Selectors & Descriptors, Hands-on automation labs

Hands-on:

1. Performing data extraction and manipulation using Data Tables and Excel automation

2. Automating web/desktop tasks using UI activities like Click and Type Into

3. Working with selectors and descriptors to handle dynamic UI elements

4. Case Study: Building an end-to-end automation for data entry from Excel to a web application

Unit 5

Advanced Automation, Debugging & RE Framework

08 hours

Recording techniques (Web, Desktop, Citrix), Debugging tools (Breakpoints, Step Into, Watch), Exception Handling (Try Catch, Logging), Project best practices, UiPath RE Framework (Robotic Enterprise Framework): Transactional Business Process Template, State Machine-based architecture, Init State: Initialize applications & settings, Get Transaction Data: Fetch queue items, Process Transaction: Execute business logic, End Process: Cleanup & reporting, Exception handling: System vs Business exceptions, Retry mechanism & queue-based processing, Logging & Orchestrator integration

Hands-on:

1. Recording and automating tasks using Web, Desktop, and Citrix recording techniques

2. Debugging workflows using breakpoints, step execution, and logs

3. Implementing exception handling using Try-Catch and logging mechanisms

4. Case Study: Developing an enterprise-level automation using RE Framework with queue processing and retry logic

Total Lecture Hours

40 hours

Textbook:

1. Learning Robotic Process Automation with UiPath – Alok Mani Tripathi

2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow – Aurélien Géron

3. Building LLM Applications with LangChain – (O’Reilly / relevant author editions)

4. Artificial Intelligence Basics: A Non-Technical Introduction – Tom Taulli

 

Reference Books:

1. Robotic Process Automation: Guide to Building Software Robots – Richard Murdoch

2. AI Engineering: Building Applications with Foundation Models – Chip Huyen

3. Generative AI with Python and TensorFlow – Joseph Babcock

4. Automation Anywhere / UiPath Official Documentation (Online Reference)

Mode of Evaluation:

Evaluation Scheme

MSE

CA

ESE

Total Marks

MSE1

MSE2

CA1

CA2

CA3

75

150

30

30

6

6

3

60

15

 

CO

Course Outcome

BL

KC

PO Mapping

CO1

Understand concepts of Generative AI, LLMs, Prompt Engineering, and RAG architecture for building intelligent systems.

2 (Understand)

K2

PO1(2), PO2(2), PO3(1), PO4(2), PO5(1), PO8(2)

CO2

Apply agentic AI concepts including agent architecture, multi-agent systems, and integration of RAG with real-time applications.

3 (Apply)

K3

PO1(2), PO2(2), PO3(2), PO4(2), PO5(2), PO8(2)

CO3

Develop automation workflows using UiPath components, variables, arguments, and control flow mechanisms.

3 (Apply)

K3

PO1(2), PO2(2), PO3(3), PO4(2), PO5(2), PO6(1), PO8(2)

CO4

Implement data manipulation, Excel automation, and UI automation using selectors and activities in UiPath.

3 (Apply)

K3

PO1(2), PO2(2), PO3(3), PO4(2), PO5(2), PO6(1), PO8(2)

CO5

Apply advanced automation techniques including debugging, exception handling, and RE Framework to build robust enterprise-level automation solutions.

3 (Apply)

K4

PO1(2), PO2(2), PO3(3), PO4(2), PO5(3), PO6(2), PO7(1), PO8(2)