Module 1

Basic concepts of Artificial Intelligence and Machine 

Learning 

1 Concept of Machine Learning and Artificial 

Intelligence: Definition, Evolution 

2 Types Of Machine Learning: Supervised learning, 

Unsupervised learning, Reinforcement learning, 

Evolutionary learning 

3 Common ML algorithms: Regression, 

Classification, Clustering. (Concepts) 

4 The Machine Learning Process: Data Collection and 

Preparation, Feature Selection , Algorithm Choice , 

Parameter and Model Selection , Training , 

Evaluation 

5 Application of Machine Learning: Healthcare, 

Finance, Self Driving Cars, Robotics 

Module 2

Introduction to Block chain Technology:

6. Cryptography Overview: Definition, Types of 

Cryptography -Public and Private Keys, Application 

-Digital Signature 

7 Introduction to Block chain Technology: History of 

Block chain, Generic Elements of Block chain, 

Features of Block chain(Decentralization, 

Transparency , Immutability and Security) 

8 Types of Block chain: 

9 Applications of Bock chain Technology : Financial 

Services, Supply Chain Management, Smart 

Contracts 

10 Crypto currencies: Definition, Bit coin, Ethereum 

 11 Challenges in Block chain Adoption: Scalability, 

interoperability, and regulatory concerns, Security 

considerations. 

Module 3

IOT and Cloud Technology 

12 Overview of Computer Networks: Definition, types, 

and importance. 

13 Network Design Concepts: ISO/OSI and TCP/IP 

14 Networking Devices and Protocols: Routers, 

switches, Hub, Modems, TCP, UDP, IP. 

15 Cloud Computing and Services: Infrastructure as a 

Service (IaaS), Platform as a Service (PaaS), and 

Software as a Service (SaaS). 

 16 Internet of Things: Definition, Key characteristic, 

Architecture and components, Challenges and 

Security in IOT. 

Module 4

Unstructured Database 

17 Overview of traditional DBMS: Relational, Object-

Oriented Database 

18 Structured and Unstructured Database 

19 Introduction to NoSQL databases 

20 Types of NoSQL databases (Document-oriented, 

Key-value stores, Column-family stores, Graph 

databases) 

 21 Cloud-Based Database Services: Database as a 

Service (DBaaS) overview, Benefits of cloud-based 

solutions 

22 Block chain Databases (2 hours): Understanding 

graph databases and their applications, Overview of 

Block chain databases and their role in data 

integrity. 

Module 5

 Practical Applications, Case Study 30

1 1. Identify the various software platforms for AI 

programming. 

 2. Identify the various platforms used for No-Code 

AI.(Google Cloud Auto ML, Microsoft Azure Al 

Buildeer, IBM Watson Studio etc..) 

3. Use chatbot platforms like ChatGPT or any other 

to engage in conversational interactions and 

understand how natural language processing works. 

4.Use online tools or any applications that 

demonstrate image recognition capabilities. 

5.Use online platforms or software that provide 

interactive AI demos and simulations, such as neural 

network visualisers or AI-powered character 

generators. 

6.Use an online tool like CyberChef or an online 

RSA key generator to generate a pair of RSA public 

and private keys. 

7. Create a digital signature for a given document 

using an online service like DocuSign or HelloSign, 

and verify it using the service's verification features. 

8. Use online resources to create a comparison table 

for public, private, and consortium blockchains, 

including real-world examples. 

9. Use MySQL or PostgreSQL to create a database, 

define tables, and perform CRUD operations. 

10.Use db4o (Database for Objects) or an equivalent 

tool to create and manipulate an object-oriented 

database. 

11. Use MongoDB to store and query unstructured 

data. 

12. Use MongoDB to create a collection and 

perform CRUD operations. 

13. Deploy and interact with a cloud-based database 

service. 

V 14. Explore and implement a basic blockchain 

database using an appropriate platform. 

15. Use BigchainDB or a similar blockchain 

database platform to create a blockchain database.