M.Tech.(Online) Admissions 2022


Application Website for Nominated Candidates: Click Here


Important Dates

Nominations received from company for their candidates 15 March 2022
Admissions portal opens for nominated candidates to apply 18 March 2022
Admissions portal closes 15 April 2022
22 April 2022 (extended)
DSBA Written Test 9 May 2022, 12:00 - 1:00PM
ECE Written Test 9 May 2022, 5:00 - 6:00PM
AI Written Test 10 May 2022, 12:00 - 1:00PM
DSBA Interviews 11 - 14 May 2022
Offer of admission to selected candidates by IISc 2 June 2022
06 July 2022
Payment of fees and deposit by selected candidates 1 July 2022
15 July 2022
Academic year starts 1 August 2022

Admission Process


Minimum Eligibility for Different Streams

Applicants must meet these minimum eligibility requirements listed below to apply to a stream. Applicants must also be nominated by their respective companies who have an MOU with IISc for this program.

Stream Minimum Degree Percentage Years in Industry Others Selection
Data Science and Business Analytics BE/BTech/BS(4yrs)/Equivalent (4-year degree/diploma after 12th standard) or Master's degree in any discipline At least 50% or equivalent CGPA in all degrees Two years at the time of joining. Strong mathematical and programming experience Online written/programming test, followed by video interview for shortlisted applicants
Artificial Intelligence BE/BTech in CS/ECE/EE or equivalent discipline At least 70% or equivalent CGPA in all degrees Two years at the time of joining. Strong mathematical and programming experience Online written test
Electronics and Communication Engineering BE/BTech in ECE/EE or equivalent discipline At least 60% or equivalent CGPA in all degrees Two years at the time of joining. Strong mathematical and programming experience Online written test


Admissions Test and Interview

All nominated candidates who have applied to the program and meet the eligibility criteria will be asked to attend an online written/programming test for the streams they have applied to. For the DSBA stream, applicants will further be shortlisted based on the written test and need to attend an online interview.



Artificial Intelligence - Syllabus for Written Test


  • Calculus: Limits, continuity and differentiability. Maxima and minima. Mean value theorem. Integration.
  • Linear Algebra: Matrices, determinants, system of linear equations, eigenvalues and eigenvectors, LU decomposition
  • Probability: Random variables. Uniform, normal, exponential, Poisson and binomial distributions. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem.

Sample Written Test



Data Science and Business Analytics - Syllabus for Written Test and Interview


  • Foundations: Linear Algebra/Matrices, Probability, Statistics and Combinatorics at the undergraduate engineering mathematics level, in addition to basic Calculus and Geometry.
  • Programming: Data Structures (arrays, matrices, etc.) and Basic Programming (choice of Java/C/C++/Python).

The online written test will contain 7 MCQ questions and 1 programming question and the duration is 60 mins.

Sample Written Test

The online interviews for candidates short-listed based on the written test will be over video conference and will last for about 30mins.



Electronics and Communication Engineering - Syllabus for Written Test


Engineering Mathematics
  • Linear Algebra: Vector space, basis, linear dependence and independence, matrix algebra, eigen values and eigen vectors, rank, solution of linear equations – existence and uniqueness.
  • Calculus: Mean value theorems, theorems of integral calculus, evaluation of definite and improper integrals, partial derivatives, maxima and minima, multiple integrals, line, Taylor series.
  • Differential Equations: First order equations (linear and nonlinear), higher order linear differential equations, methods of solution using variation of parameters, complementary function and particular integral, partial differential equations, variable separable method, initial and boundary value problems.
  • Vector Analysis: Vectors in plane and space, vector operations, gradient, divergence and curl
  • Probability and Statistics: Mean, median, mode and standard deviation; combinatorial probability, probability distribution functions - binomial, Poisson, exponential and normal; Joint and conditional probability; Correlation and Random processes: autocorrelation and power spectral density, properties of white noise
Communications
  • Information theory: entropy, mutual information and channel capacity theorem;
  • Digital communications: digital modulation schemes, amplitude, phase and frequency shift keying (ASK, PSK, FSK), QAM, MAP and ML decoding, matched filter receiver, SNR and BER for digital modulation;
Signal Processing
  • Continuous-time signals: Fourier series and Fourier transform representations, Laplace transform, sampling theorem and applications;
  • Discrete-time signals: discrete-time Fourier transform (DTFT), DFT, FFT, Z-transform, interpolation of discrete-time signals;
  • LTI systems: definition and properties, causality, stability, impulse response, convolution, poles and zeros, parallel and cascade structure, frequency response, Transient and steady-state analysis
  • Basic control system components; Feedback principle; Transfer function; Block diagram representation;
HFCS
  • Devices: Energy bands in intrinsic and extrinsic silicon; Carrier transport: diffusion current, drift current, mobility and resistivity;
  • Analog circuits: Small signal equivalent circuits of diodes, BJTs and MOSFETs; Simple diode circuits: clipping, clamping and rectifiers; Single-stage BJT and MOSFET amplifiers: biasing, bias stability, mid-frequency small signal analysis and frequency response; Simple op-amp circuits
  • Digital circuits: Number systems; Combinatorial circuits: Boolean algebra, minimization of functions using Boolean identities and Karnaugh map, logic gates and their static CMOS implementations, arithmetic circuits, multiplexers, Sequential circuits: latches and flip‐flops, counters, shift‐registers and finite state machines;
  • Electromagnetic: Maxwell’s equations: differential and integral forms and their interpretation, boundary conditions, wave equation, Poynting vector; Transmission lines: equations, characteristic impedance, propagation constant, impedance matching, impedance transformation, S-parameters

Sample Written Test