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Machine Learning Techniques (BCS055) AKTU exam strategy

Focus on Unit 2 (Regression, Bayesian Learning and Support Vector Machine) and Unit 3 (Decision Tree Learning and Instance-Based Learning). Together they account for about 59 marks among all questions printed per paper. Unit 1 (Introduction) is safest to skim if you're short on time.

Unit priority

  • Unit 2 (Regression, Bayesian Learning and Support Vector Machine) – Must Prepare, 34 marks avg. Unit 2 (Regression, Bayesian Learning and Support Vector Machine) averages 34 marks per paper — one of the heaviest units in this subject. Must-do: Logistic Regression, Naive Bayes Classifier, Expectation-Maximization Algorithm, Types of Support Vector Kernels.
  • Unit 3 (Decision Tree Learning and Instance-Based Learning) – High Priority, 25 marks avg. Unit 3 (Decision Tree Learning and Instance-Based Learning) averages 25 marks per paper — one of the heaviest units in this subject. Must-do: Issues in Decision Tree Learning, k-Nearest Neighbour Learning, ID-3 Algorithm, Locally Weighted Regression.
  • Unit 5 (Reinforcement Learning and Genetic Algorithms) – High Priority, 24 marks avg. Unit 5 (Reinforcement Learning and Genetic Algorithms) averages 24 marks per paper — one of the heaviest units in this subject. GA Cycle of Reproduction has appeared in every paper analysed — these are must-dos. Must-do: Q Learning, GA Cycle of Reproduction, Introduction to Reinforcement Learning, Markov Decision Process.
  • Unit 4 (Artificial Neural Networks and Deep Learning) – Medium Priority, 23 marks avg. Unit 4 (Artificial Neural Networks and Deep Learning) averages 23 marks per paper — one of the heaviest units in this subject. Must-do: Derivation of Backpropagation Algorithm, Types of CNN Layers, Concept of Convolutional Neural Network, Gradient Descent and the Delta Rule.
  • Unit 1 (Introduction) – Safe to Skim, 17 marks avg. Unit 1 (Introduction) averages 17 marks per paper — one of the heaviest units in this subject. Types of Learning has appeared in every paper analysed — these are must-dos. Must-do: Types of Learning, Well-Defined Learning Problems, Designing a Learning System, Introduction to Machine Learning Approaches.

Topics AKTU keeps repeating

  • Types of Learning: Asked in 6 out of 9 papers. If you prepare only one topic from its unit, make it this one.
  • GA Cycle of Reproduction: Asked in 6 out of 9 papers. If you prepare only one topic from its unit, make it this one.

Short on time?

  • Among all units, Unit 1 (Introduction) is the lowest priority at 17M avg. If you're running low on time, prioritize the top 3 units and give this one a quick read. But even here — Types of Learning, Well-Defined Learning Problems, Introduction to Machine Learning Approaches are high-repeat topics. Cover these at minimum to stay safe.

How the paper is marked

  • Section A: 7 questions × 2 marks = 14 marks. Short definition/concept questions from all 5 units. Prepare 2–3 key definitions per unit — this section is the easiest 14 marks you can secure.
  • Section B: Attempt any 3 of 5 questions × 7 marks = 21 marks. Choose the 3 questions from units you've prepared most. Don't attempt all 5 — pick your strongest 3 and write them well.
  • Section C: 5 OR-pairs × 7 marks = 35 marks. One pair per unit — you must attempt all 5. This is where the exam is won or lost. Focus your deep preparation on the top 3 priority units.

Exam-day tips

  • Start with Section A to build momentum — budget 15–20 minutes max for all 7 questions.
  • In Section B, Unit 2 (Regression, Bayesian Learning and Support Vector Machine) questions have the highest repeat rate — always attempt that one first.
  • For Section C OR-pairs, read both options before choosing — sometimes the 'b' option is simpler despite appearing longer.
  • If you've prepared the VERY LIKELY topics, you can comfortably score 50+ marks without touching any new topic on exam day.
  • This strategy is built on 9 past papers — the patterns here are highly reliable.