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Important topic of All subject : CLICK HERE
NOTE : This content was generated with the assistance of AI. While it has been carefully reviewe. Use it as a study aid, not a sole source.
This detailed analysis of past year questions and syllabus breakdown will help you focus on the most important topics, their marks distribution, and exam trends!
This comprehensive breakdown of past-year questions, syllabus weightage, and key trends will streamline your exam prep!
🔥 What’s Covered?
✔ Chapter-wise Important Topics – Focus on high-yield concepts.
✔ Marks Distribution – Know where to invest your time.
✔ Exam Patterns – Identify frequently repeated questions.
✔ Solved Examples & Strategies – Master problem-solving techniques.
Subject Highlights:
1️⃣ Numerical Methods
🔹 Root Finding: Newton-Raphson, Secant, Bisection Methods
🔹 Interpolation: Lagrange, Newton’s Divided Difference
🔹 Linear Systems: LU Decomposition, Gauss-Jordan, Iterative Methods
🔹 Integration & ODEs: Simpson’s Rule, Runge-Kutta 4th Order
2️⃣ Computer Architecture
🔹 Pipelining: Hazards, 4-Segment Instruction Cycle
🔹 Cache Mapping: Direct, Associative, Set-Associative
🔹 I/O Systems: DMA, Interrupt Handling (Polling vs. Parallel)
🔹 Arithmetic: Booth’s Algorithm, Non-Restoring Division
3️⃣ Computer Graphics
🔹 Scan Conversion: Bresenham’s Line, Mid-Point Circle
🔹 Transformations: 2D/3D Homogeneous Coordinates
🔹 Visible Surface Detection: Z-Buffer, Painter’s Algorithm
🔹 Illumination Models: Phong vs. Gouraud Shading
4️⃣ Data Structures & Algorithms (DSA)
🔹 Sorting: QuickSort, MergeSort, HeapSort
🔹 Searching: Binary Search, Hashing (Linear/Quadratic Probing)
🔹 Trees: AVL Balancing, BSP Trees, Huffman Coding
🔹 Graphs: Dijkstra’s, MST (Prim’s/Kruskal’s)
5️⃣ Statistics II
🔹 Regression: Multiple Linear Regression, Partial Correlation
🔹 Hypothesis Testing: t-tests, ANOVA (CRD, RBD, LSD)
🔹 Non-Parametric Tests: Kruskal-Wallis, Chi-Square
🔹 Stochastic Processes: Markov Chains, Queuing Theory (M/M/1)
🎯 Why Use This Guide?
✅ Saves Time – Prioritize high-weightage topics.
✅ Exam-Oriented – Covers repeated questions & trends.
✅ Clear Explanations – Algorithms, derivations, and numericals simplified.
✅ Last-Minute Ready – Short notes on key formulas and concepts.
📥 How to Use?
1️⃣ Start with high-mark chapters (e.g., Pipelining, Regression, AVL Trees).
2️⃣ Practice derivations & numericals (e.g., Booth’s Multiplication, Bresenham’s Algorithm).
3️⃣ Revise definitions & comparisons (e.g., RISC vs. CISC, Phong vs. Gouraud).
💬 Need clarifications? Ask below!
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