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DINESH KUMAR

Student Profile

Dinesh Kumar

Hello, I'm Dinesh Kumar

I am a B.Tech student pursuing Artificial Intelligence and Data Science (AIDS) at Amrita Vishwa Vidyapeetham. Currently in my First Semester.

This portfolio serves as my academic dashboard, featuring my class schedule, detailed syllabus curriculum, and direct access to my study materials.

Fall 2025 Schedule

Class: I-SEM-B.Tech-AI-DS | Room: 16
TimeMondayTuesdayWednesdayThursdayFriday
08:00 - 08:50Evaluation
08:50 - 09:4023EEE103
Intro Elec. Eng.
23PHY104
Comp. Mech 1
23AID102
Elements Comp 1
23BIO112
Intro Bio Data
23PHY104
Comp. Mech 1
09:40 - 10:3023MAT106
Maths Intel Sys
23AID101
Comp. Thinking
23EEE103
Intro Elec. Eng.
23MAT106
Maths Intel Sys
23AID101
Comp. Thinking
10:30 - 10:45Morning Break
10:45 - 11:3523BIO112
Intro Bio Data
23AID102
Elements Comp 1
22AVP103
Mastery Mind
23AID101
Comp. Thinking
23BIO112
Intro Bio Data
11:35 - 12:2523AID102
Elements Comp 1
23EEE103 (Lab)
Elec. Eng.
22AVP103
Mastery Mind
23PHY104
Comp. Mech 1
23MAT106
Maths Intel Sys
12:25 - 01:1522ADM101
Indian Heritage
23EEE103 (Lab)
Elec. Eng.
22ADM101
Indian Heritage
23EEE103
Elec. Eng.
Project/Lab
01:15 - 02:05Lunch Break
02:05 - 02:5523PHY104 (Lab)
Comp. Mech 1
TestTestTestTest
02:55 - 04:3523PHY104 (Lab)23BIO112 (Lab)
Bio Data
23MAT106 (Lab)
Maths Intel Sys
23AID102 (Lab)
Elements Comp 1
23AID101 (Lab)
Comp. Thinking
Project/Lab

Syllabus & Curriculum

Select a subject below to view detailed syllabus units and evaluation patterns.

23MAT106

Maths for Intelligent Systems 1

Credits: 4 | Semester: 1

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23PHY104

Computational Mechanics 1

Credits: 3 | Semester: 1

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23AID101

Computational Thinking

Credits: 3 | Semester: 1

View Syllabus
23AID102

Elements of Computing 1

Credits: 3 | Semester: 1

View Syllabus
23EEE103

Intro to Electrical Engineering

Credits: 3 | Semester: 1

View Syllabus
22AVP103

Mastery Over Mind

Credits: 2 | Semester: 1

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22ADM101

Foundations of Indian Heritage

Credits: 2 | Semester: 1

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23BIO112

Introduction to Biological Data

Credits: 3 | Semester: 1

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Mathematics for Intelligent Systems 1

Unit 1

Basics of Linear Algebra – Linear Dependence and independence of vectors – Gaussian Elimination – Rank of set of vectors forming a matrix – Vector space and Basis set for a Vector space – Dot product and Orthogonality -CR decomposition – Rotation matrices – Eigenvalues and Eigenvectors and its interpretation-Introduction to SVD-Computational experiments using Matlab/Excel/Simulink.

Unit 2

Ordinary Linear differential equations, formulation – concept of slope, velocity and acceleration – analytical and numerical solutions- Impulse Response computations- converting higher order into first order equations – examples of ODE modelling in falling objects, satellite and planetary motion, Electrical and mechanical systems– Introduction to solving simple differential equations with Simulink- Introduction to one variable optimization – Taylor series- Computational experiments using Matlab /Excel/Simulink.

Unit 3

Introduction to random variables (continuous and discrete), mean, standard deviation, variance, sum of independent random variable, convolution, sum of convolution integral, probability distributions.

Unit 4

Introduction to quantum computing, Quantum Computing Roadmap, Quantum Mission in India, A Brief Introduction to Applications of Quantum computers, Quantum Computing Basics, Bracket Notation, Inner product, outer product, concept of state.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Assignments (Min 2)Internal30
Quizzes (Min 2)Internal20
Mid-Term ExaminationInternal20
Term Project / End SemExternal30
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Computational Mechanics 1

Unit 1: Kinematics and Statics

Position, velocity, and acceleration of particles, Newton’s laws of motion, Work and energy, Rigid body kinematics, Translations and Rotations, Alternate representations of Rigid body Rotation – Rotation matrices, Euler angles, Axis-angle representations, Quaternions. Introduction to statics and equilibrium, Free body diagrams, Equilibrium of particles and rigid bodies, Computational aspects of solving kinematics and statics problems of real world systems.

Unit 2: Introduction to Kinetics

Cross product of two vectors, Inertial and Non-Inertial frame of reference, Linear momentum, Center of mass, Coriolis, Inertial and Centripetal forces, Acceleration in polar coordinates, Angular velocity, Angular momentum and Torque on particles, Computational aspects of solving kinetics problems of particles.

Unit 3: Kinetics of Rigid Bodies

Two particle system angular momentum, Inertia matrix, Moment and product of inertia, Principal axes theorem, Principal axes as eigenvector of Inertia matrix, Parallel axes theorem, Computational aspects of solving kinetics problems of particles, Introduction to Euler-Lagrange and Newton-Euler equations for solving rigid body dynamics. Euler-Lagrange equation derivation using one dimensional point mass example, Application of Euler-Lagrange equation for solving dynamics of simple mechanical systems.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Assignments (Min 2)Internal30
Quizzes (Min 2)Internal20
Mid-Term ExaminationInternal20
Term Project / End SemExternal30
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Computational Thinking

Unit 1

Computational Thinking, critical thinking, data representation, abstraction, decomposition- breaking problems into parts, basic data types, pseudocode, algorithms-methods to solve the problems, brute-force or exhaustive search problems, divide and conquer problems

Unit 2

Computational Thinking using spreadsheets, basic operations, cell references – relative and absolute, lookup operations, implement fractals – newton, Sierpinski triangle, L-system fractals, solve calculus based problems using spreadsheet, using spreadsheet for solving probability related problems

Unit 3

Computational thinking using matlab, basic operations, plotting of vectors, array and matrix operations, implement fractals – newton, Sierpinski triangle, L-system fractals, solve calculus based problems using matlab, using matlab for solving probability related problems

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Assignments (Min 2)Internal30
Quizzes (Min 2)Internal20
Mid-Term ExaminationInternal20
Term Project / End SemExternal30
← Back to Curriculum

Elements of Computing 1

Unit 1

Number System, Conversions, Signed and Unsigned Binary Number Representation, Boolean algebra and Karnaugh Maps, Logic gates, Realization of basic gates using universal gates, Boolean function synthesis, Introduction to Hardware simulator platform Nand2teris, Hardware description language, Implementation of basic gates and its multi-bit and multiway versions in Nand2teris software suite.

Unit 2

Combinational Logic, Half Adder, Full Adder, Multiplexer and demultiplexer, Multi-bit and Multiway versions, Realization of Boolean functions using combinational logic, Arithmetic logic unit (ALU)-specification, design, Sequential logic, Flip Flops, Registers, RAM, ROM.

Unit 3

Von-Neumann architecture, Program Counter, Central Processing unit, Data Memory, Hack machine language specifications/ instructions for CPU design, Hack CPU Design, CPU Control logic, building a Hack Computer.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Assignments (Min 2)Internal30
Quizzes (Min 2)Internal20
Mid-Term ExaminationInternal20
Term Project / End SemExternal30
← Back to Curriculum

Intro to Electrical Engineering

Unit 1: DC Circuit

EMF, Charge, Voltage, Current – Linear circuit elements – Energy and power – Ohms law – Kirchhoff’s voltage and current law – Series parallel combination of R, L, C components – Voltage divider and current divider rules – Super position theorem – Nodal and Mesh Analysis – Step response of RL and RC Circuits (Transient behaviour) – Equivalent network: Thevenin and Norton.

Unit 2: AC Circuit

Impedance – Instantaneous, Average, Active, Reactive and Apparent Power – Power Factor – Phasors

Unit 3: Introduction to Control Systems

State Space Representation: State, State variable, and State Model – Canonical state space model for Series RLC Circuit – Solution using eigen values and eigen vectors.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Assignments (Min 2)Internal30
Quizzes (Min 2)Internal20
Mid-Term ExaminationInternal20
Term Project / End SemExternal30
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Mastery Over Mind

Unit I: Describe Meditation and Understand its Benefits

A: Importance of meditation. How does meditation help to overcome obstacles in life. B: Understand how meditation works. Understand how meditation helps in improving physical and mental health. Understand how meditation helps in the development of personality.

Unit II: Causes of Stress and How Meditation Improves Well-being

A: Learn how to prepare for meditation. Understand the aids that can help in effectively practicing meditation. Understand the role of sleep, physical activity, and a balanced diet in supporting meditation. B: Causes of Stress. The problem of not being relaxed. Effects of stress on health. How meditation helps to relieve stress. Basics of stress management at home and the workplace.

Unit III: The Science of Meditation

A: A preliminary understanding of the Science of meditation. What can modern science tell us about this tradition-based method? B: How meditation helps humanity according to what we know from scientific research

Unit IV: Practicing MA OM Meditation in Daily Life

Guided Meditation Sessions following scripts provided (Level One to Level Five)

Unit V: Improving Communication and Relationships

How meditation and mindfulness influence interpersonal communication. The role of meditation in improving relationship quality in the family, at the university and in the workplace.

Unit VI: Meditation and Compassion-driven Action

Understand how meditation can help to motivate compassion-driven action.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Continuous Assessment (CA)Internal80
End SemesterExternal20
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Foundations of Indian Heritage

Overview

Educational Heritage of Ancient India, Life and Happiness, Impact of Colonialism and Decolonization, A timeline of Early Indian Subcontinent, Pinnacle of Selflessness and ultimate freedom, Indian approach towards life, Circle of Life, Ocean of love; Indian Mahatmas, Man’s association with Nature, Celebrating life 24/7, Metaphors and Tropes, Become A Strategic Thinker (Games / Indic activity), India: In the Views of Other Scholars and Travellers, Personality Development Through Yoga, Hallmark of Indian Traditions: Advaita Vedanta, Theory of oneness, Conversations on Compassion with Amma.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Continuous Assessment (CA)Internal30
Mid-SemesterInternal30
End SemesterExternal40
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Introduction to Biological Data

Course Overview

Introduction to biological datasets, bioinformatics, and data analysis techniques relevant to AI/DS.

Evaluation Pattern

AssessmentInternal/ExternalWeightage (%)
Assignments (Min 2)Internal30
Quizzes (Min 2)Internal20
Mid-Term ExaminationInternal20
Term Project / End SemExternal30

Course Notes

Select a subject below to access cloud-hosted study materials.

23MAT106

Maths for Intelligent Systems 1

Open Drive Links
23PHY104

Computational Mechanics 1

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23AID101

Computational Thinking

Open Drive Links
23AID102

Elements of Computing 1

Open Drive Links
23EEE103

Intro to Electrical Engineering

Open Drive Links
23BIO112

Intro to Biological Data

Open Drive Links
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Maths Resources

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Physics Resources

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Thinking Resources

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Elements Resources

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EEE Resources

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Bio Resources