316313-EMERGING TRENDS IN COMPUTER ENGINEERIN... https://services.msbte.edu.in/scheme_digi/pdfdownload/d...
21-09-2025 04:08:53 PM
EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY
Course Code : 316313
: Cloud Computing and Big Data/ Computer Technology/ Computer Engineering/
Computer Science & Engineering/
Programme Name/s
Computer Hardware & Maintenance/ Information Technology/ Computer Science &
Information Technology/ Computer Science/
Programme Code : BD/ CM/ CO/ CW/ HA/ IF/ IH/ SE
Semester : Sixth
: EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION
Course Title
TECHNOLOGY
Course Code : 316313
I. RATIONALE
Emerging trends in Computer Engineering and Information Technology are driven by the need for efficiency,
security and automation. Technologies like AI, cloud computing, IoT, and blockchain enhance productivity and
connectivity. Digital forensics is essential for investigating cybercrimes, while green computing promotes
sustainability. This course creates awareness in students regarding emerging trends in the area of Computer
Engineering and Information Technology.
II. INDUSTRY / EMPLOYER EXPECTED OUTCOME
The aim of this course is to help the students to attain following Industry Identified Outcome through various
Teaching Learning experiences : Create awareness of latest trends in Computer Engineering and Information
Technology.
III. COURSE LEVEL LEARNING OUTCOMES (COS)
Students will be able to achieve & demonstrate the following COs on completion of course based learning
• CO1 - Elaborate the role of Artificial Intelligence ,Machine Learning and Deep Learning in various domains.
• CO2 - Compare the architecture of IoT in Local environment vs Cloud Environment.
• CO3 - Explain the functioning of Blockchain Technology in various applications considering different
challenges.
• CO4 - Explain characteristics of different Immersive Technologies.
• CO5 - Identify the appropriate Model of Digital Forensic Investigation for given situation.
IV. TEACHING-LEARNING & ASSESSMENT SCHEME
Learning Scheme Assessment Scheme
Actual
Contact Based on LL &
Hrs./ Based on
Course Theory TL
Course SL
Course Title Abbr Category/ Week Credits Paper Total
Code SLH NLH
s Duration Practical Marks
FA- SA-
CL TL LL Total FA-PR SA-PR SLA
TH TH
Max Max Max Min Max Min Max Min Max Min
EMERGING
TRENDS IN
COMPUTER
316313 ENGINEERING ETI DSC 3 - - 1 4 2 1.5 30 70*# 100 40 - - - - 25 10 125
AND
INFORMATION
TECHNOLOGY
Total IKS Hrs for Sem. : 0 Hrs
Abbreviations: CL- ClassRoom Learning , TL- Tutorial Learning, LL-Laboratory Learning, SLH-Self Learning
Hours, NLH-Notional Learning Hours, FA - Formative Assessment, SA -Summative assessment, IKS - Indian
Knowledge System, SLA - Self Learning Assessment
Legends: @ Internal Assessment, # External Assessment, *# On Line Examination , @$ Internal Online
Examination
Note :
MSBTE Approval Dt. 04/09/2025 Semester - 6, K Scheme
1 of 7 21/09/25, 16:09
,316313-EMERGING TRENDS IN COMPUTER ENGINEERIN... https://services.msbte.edu.in/scheme_digi/pdfdownload/d...
21-09-2025 04:08:53 PM
EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY
Course Code : 316313
1. FA-TH represents average of two class tests of 30 marks each conducted during the semester.
2. If candidate is not securing minimum passing marks in FA-PR of any course then the candidate shall be
declared as "Detained" in that semester.
3. If candidate is not securing minimum passing marks in SLA of any course then the candidate shall be
declared as fail and will have to repeat and resubmit SLA work.
4. Notional Learning hours for the semester are (CL+LL+TL+SL)hrs.* 15 Weeks
5. 1 credit is equivalent to 30 Notional hrs.
6. * Self learning hours shall not be reflected in the Time Table.
7. * Self learning includes micro project / assignment / other activities.
V. THEORY LEARNING OUTCOMES AND ALIGNED COURSE CONTENT
Theory Learning Suggested
Learning content mapped with Theory Learning
Sr.No Outcomes Learning
Outcomes (TLO's) and CO's.
(TLO's)aligned to CO's. Pedagogies.
TLO 1.1 Describe the
concept of Al.
TLO 1.2 List
applications of Al. Unit - I Introduction of AI and ML
TLO 1.3 Define Machine 1.1 Introduction of AI :Concept ,Scope of Al, Types of AI,
Learning. Applications of AI
TLO 1.4 Describe 1.2 Machine Learning: Concept, Types: Supervised,
characteristics of Unsupervised, Reinforcement, Applications of Machine
different types of Learning, Concept of Deep Learning, Applications of Deep
Machine learning. Learning ,Concept of Neural Network, Difference between
TLO 1.5 Describe the AI, ML and DL
Presentations
concept of Deep 1.3 Generative AI: Concept ,Transformers: Key components
Case Study
learning. of Transformers: Self-attention mechanism, Multi-head
Lecture Using
1 TLO 1.6 Describe attention, Positional encoding, Feed forward Neural
Chalk-Board
importance of Neural Network, Layer Normalization, Encoder Decoder Structure,
Video
Network. Types of Generative AI: Text Generation, Image Generation,
Demonstrations
TLO 1.7 Differentiate the Music and Audio Generation, Video Generation
concepts of AI, ML ad ,Applications of Generative AI
DL. 1.4 AI & ML in Digital security :Types of attacks : AI
TLO 1.8 Explain the Powered cyber attack, Adversarial AI attacks, Evasion AI
function of different key Attack, AI poisoning attack, AI powered attacks protection
components of measures: Turn on Multi-Factor Authentication, Use Super
Generative AI. Strong Password, Update Everything, Secure your Network,
TLO 1.9 Describe the Use your mobile Device Securely
role of AI & ML to
improve the effectiveness
of security mechanisms.
2 TLO 2.1 Describe the Unit - II Internet of Things Presentations
concept of IoT. 2.1 Introduction of Internet of Things (loT): Definition, Lecture Using
TLO 2.2 Write features Characteristics of loT, Features and Application of loT, Chalk-Board
and applications of IoT. Advantages and limitations of IoT Flipped
TLO 2.3 List the 2.2 Design of loT: Physical design of IoT, Logical design of Classroom
advantages and loT, Architecture of Internet of Things (IoT)
Limitations of IoT. 2.3 Sensors and actuators used in IoT
TLO 2.4 Explain the 2.4 5G Network in IOT communication: 5-G characteristics
architecture of IoT in and application areas, Next Generation Network:
local environment. Architecture, Features, Functional block diagram, Network
TLO 2.5 Describe the components: Media Gateway, Media Gateway Controller and
function of Sensors and Application Server
actuators used in IoT. 2.5 IoT and Cloud Computing: Architecture of Cloud based
TLO 2.6 Explain NGN IoT
MSBTE Approval Dt. 04/09/2025 Semester - 6, K Scheme
2 of 7
21/09/25, 16:09
21-09-2025 04:08:53 PM
EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY
Course Code : 316313
: Cloud Computing and Big Data/ Computer Technology/ Computer Engineering/
Computer Science & Engineering/
Programme Name/s
Computer Hardware & Maintenance/ Information Technology/ Computer Science &
Information Technology/ Computer Science/
Programme Code : BD/ CM/ CO/ CW/ HA/ IF/ IH/ SE
Semester : Sixth
: EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION
Course Title
TECHNOLOGY
Course Code : 316313
I. RATIONALE
Emerging trends in Computer Engineering and Information Technology are driven by the need for efficiency,
security and automation. Technologies like AI, cloud computing, IoT, and blockchain enhance productivity and
connectivity. Digital forensics is essential for investigating cybercrimes, while green computing promotes
sustainability. This course creates awareness in students regarding emerging trends in the area of Computer
Engineering and Information Technology.
II. INDUSTRY / EMPLOYER EXPECTED OUTCOME
The aim of this course is to help the students to attain following Industry Identified Outcome through various
Teaching Learning experiences : Create awareness of latest trends in Computer Engineering and Information
Technology.
III. COURSE LEVEL LEARNING OUTCOMES (COS)
Students will be able to achieve & demonstrate the following COs on completion of course based learning
• CO1 - Elaborate the role of Artificial Intelligence ,Machine Learning and Deep Learning in various domains.
• CO2 - Compare the architecture of IoT in Local environment vs Cloud Environment.
• CO3 - Explain the functioning of Blockchain Technology in various applications considering different
challenges.
• CO4 - Explain characteristics of different Immersive Technologies.
• CO5 - Identify the appropriate Model of Digital Forensic Investigation for given situation.
IV. TEACHING-LEARNING & ASSESSMENT SCHEME
Learning Scheme Assessment Scheme
Actual
Contact Based on LL &
Hrs./ Based on
Course Theory TL
Course SL
Course Title Abbr Category/ Week Credits Paper Total
Code SLH NLH
s Duration Practical Marks
FA- SA-
CL TL LL Total FA-PR SA-PR SLA
TH TH
Max Max Max Min Max Min Max Min Max Min
EMERGING
TRENDS IN
COMPUTER
316313 ENGINEERING ETI DSC 3 - - 1 4 2 1.5 30 70*# 100 40 - - - - 25 10 125
AND
INFORMATION
TECHNOLOGY
Total IKS Hrs for Sem. : 0 Hrs
Abbreviations: CL- ClassRoom Learning , TL- Tutorial Learning, LL-Laboratory Learning, SLH-Self Learning
Hours, NLH-Notional Learning Hours, FA - Formative Assessment, SA -Summative assessment, IKS - Indian
Knowledge System, SLA - Self Learning Assessment
Legends: @ Internal Assessment, # External Assessment, *# On Line Examination , @$ Internal Online
Examination
Note :
MSBTE Approval Dt. 04/09/2025 Semester - 6, K Scheme
1 of 7 21/09/25, 16:09
,316313-EMERGING TRENDS IN COMPUTER ENGINEERIN... https://services.msbte.edu.in/scheme_digi/pdfdownload/d...
21-09-2025 04:08:53 PM
EMERGING TRENDS IN COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY
Course Code : 316313
1. FA-TH represents average of two class tests of 30 marks each conducted during the semester.
2. If candidate is not securing minimum passing marks in FA-PR of any course then the candidate shall be
declared as "Detained" in that semester.
3. If candidate is not securing minimum passing marks in SLA of any course then the candidate shall be
declared as fail and will have to repeat and resubmit SLA work.
4. Notional Learning hours for the semester are (CL+LL+TL+SL)hrs.* 15 Weeks
5. 1 credit is equivalent to 30 Notional hrs.
6. * Self learning hours shall not be reflected in the Time Table.
7. * Self learning includes micro project / assignment / other activities.
V. THEORY LEARNING OUTCOMES AND ALIGNED COURSE CONTENT
Theory Learning Suggested
Learning content mapped with Theory Learning
Sr.No Outcomes Learning
Outcomes (TLO's) and CO's.
(TLO's)aligned to CO's. Pedagogies.
TLO 1.1 Describe the
concept of Al.
TLO 1.2 List
applications of Al. Unit - I Introduction of AI and ML
TLO 1.3 Define Machine 1.1 Introduction of AI :Concept ,Scope of Al, Types of AI,
Learning. Applications of AI
TLO 1.4 Describe 1.2 Machine Learning: Concept, Types: Supervised,
characteristics of Unsupervised, Reinforcement, Applications of Machine
different types of Learning, Concept of Deep Learning, Applications of Deep
Machine learning. Learning ,Concept of Neural Network, Difference between
TLO 1.5 Describe the AI, ML and DL
Presentations
concept of Deep 1.3 Generative AI: Concept ,Transformers: Key components
Case Study
learning. of Transformers: Self-attention mechanism, Multi-head
Lecture Using
1 TLO 1.6 Describe attention, Positional encoding, Feed forward Neural
Chalk-Board
importance of Neural Network, Layer Normalization, Encoder Decoder Structure,
Video
Network. Types of Generative AI: Text Generation, Image Generation,
Demonstrations
TLO 1.7 Differentiate the Music and Audio Generation, Video Generation
concepts of AI, ML ad ,Applications of Generative AI
DL. 1.4 AI & ML in Digital security :Types of attacks : AI
TLO 1.8 Explain the Powered cyber attack, Adversarial AI attacks, Evasion AI
function of different key Attack, AI poisoning attack, AI powered attacks protection
components of measures: Turn on Multi-Factor Authentication, Use Super
Generative AI. Strong Password, Update Everything, Secure your Network,
TLO 1.9 Describe the Use your mobile Device Securely
role of AI & ML to
improve the effectiveness
of security mechanisms.
2 TLO 2.1 Describe the Unit - II Internet of Things Presentations
concept of IoT. 2.1 Introduction of Internet of Things (loT): Definition, Lecture Using
TLO 2.2 Write features Characteristics of loT, Features and Application of loT, Chalk-Board
and applications of IoT. Advantages and limitations of IoT Flipped
TLO 2.3 List the 2.2 Design of loT: Physical design of IoT, Logical design of Classroom
advantages and loT, Architecture of Internet of Things (IoT)
Limitations of IoT. 2.3 Sensors and actuators used in IoT
TLO 2.4 Explain the 2.4 5G Network in IOT communication: 5-G characteristics
architecture of IoT in and application areas, Next Generation Network:
local environment. Architecture, Features, Functional block diagram, Network
TLO 2.5 Describe the components: Media Gateway, Media Gateway Controller and
function of Sensors and Application Server
actuators used in IoT. 2.5 IoT and Cloud Computing: Architecture of Cloud based
TLO 2.6 Explain NGN IoT
MSBTE Approval Dt. 04/09/2025 Semester - 6, K Scheme
2 of 7
21/09/25, 16:09
