LECTURE # 1 (1 APRIL) ORIENTATION

LECTURE # 2 Definition, Types of Data, Importance of data

LECTURE # 3 Categories of Data, Sources Of Data

LECTURE # 4 Ethical Considerations, Mcqs

LECTURE # 5 Revision Ch-1

LECTURE # 6 (7 APRIL): Intro to data analytics, Data Analytics Cycle

LECTURE # 7 (8 APRIL): Comprehensive example, Case study of data analytics cycle, Data Analytical Stages.

LECTURE # 8 (9 APRIL): Applications, Implications & MCQs

LECTURE # 9 (10 APRIL): Introduction, Sources and Methods of Big Data

LECTURE # 10 (11 APRIL): Applications, Challanges & MCQS of Big Data

LECTURE # 11 (13 APRIL) Chapter 4 Revision

LECTURE # 12 (14 APRIL) What is Data Governance, Key objectives of Data Governance

LECTURE # 13 (15 APRIL) "Key Components of Data Governance (topic# 1,2,3,6) Unit 6&7 (Data stewardship and Metadata Management Revision Chapter - 1, 3 & 4"

LECTURE # 13 (15 APRIL) Revision Session

LECTURE # 14 (16 APRIL) "Key Components of Data Governance, Data security, Data security practices Emerging threats and solutions."

LECTURE # 15 (17 APRIL) Levels Of Data Governance, Data Classification Models, Data Storage

LECTURE # 16 (18 APRIL) "Data Integrity Emerging Technology Compliance"

LECTURE # 16 (18 APRIL) "Data Integrity Emerging Technology Compliance"

LECTURE # 16 (18 APRIL) "Data Integrity Emerging Technology Compliance"

LECTURE # 17 (20 APRIL) Chapter Revision

lecture 18 ( 21 APRIL) Into to DBMS, Compoent of DBMS, DATABASE Characterstic, Atomicity

LECTURE # 19 (22 APRIL) Consistency, Isolation, Durability, Additional Characteristics, DBMS architecture

LECTURE # 20 (23 APRIL) Types of Data independence, Comparison table, Key benefits of 3 lvl architecture.

LECTURE # 21 (24 APRIL) PART A

LECTURE # 21 (24 APRIL) PART B (CHAPTER 2)

LECTURE # 22 (27 APRIL) Data Warehouse

LECTURE # 23 (28 APRIL) OLTP & OLAP, Data Mart, ETL process.

LECTURE # 24 (29 APRIL) Data Normalization.

LECTURE # 25 (30 APRIL) MCQs

LECTURE # 26 (01 MAY) (CHAPTER 6) Revision

LECTURE # 27 (02 MAY) PART A (CHAPTER 5) Revision

LECTURE # 27 (02 MAY) PART B (CHAPTER 5) MCQs

LECTURE # 28 (04 MAY) Introduction to IT system architecture, Key components, Scalability and Flexibility.

LECTURE # 29 (05 MAY) IT System Interaction & Independance , 5 Best Practices for design IT System

LECTURE # 30 (06 MAY) Introduction to Programming Languages

LECTURE # 31 (07 MAY) PART A (Latest trends in IT system)

LECTURE # 31 (07 MAY) PART B (Into to ERP system)

LECTURE # 32 (08 MAY) "Key components of an ERP system, ERP Implementation Cycle, Benefits of ERP Systems Types of ERP Systems"

LECTURE # 33 (09 MAY) "Key Considerations when choosing an ERP system, Challenges in Implementing ERP Systems ERP in Industries"

LECTURE # 34 (11 MAY): Revision

LECTURE # 35 (12 MAY): AI and ML

LECTURE 36 (13 MAY): IoT Devices

LECTURE 37 (14 MAY): 5G Technology, AR&VR, Edge Computung

LECTURE 38 (15 MAY) PART A: Quantum Computing and RPA

LECTURE 38 (15 MAY) PART B: Revision Chapter 09

LECTURE 39 (16 MAY): Revision Chapter 08

LECTURE 40 ( 18 MAY): AI, AI learning cycle, Types of AI.

LECTURE 41 ( 19 MAY) Algorithms Used In Generative AI, Neural Networks, Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs)

lecture 42 ( 20 may) Transformal Model,

LECTURE 43 ( 21 MAY) Agenting AI, MCQ

LECTURE 44 (1 JUNE) Understanding digital disruption, Drivers of Digital Disruption.

LECTURE 45 (3 JUNE) Impact of Digital Disruption on Businesses

LECTURE 46 (4 JUNE)

LECTURE 47 ( 5 JUNE)

LECTURE 48 ( 6 JUNE)