skilldevelopment.cpe@lpu.co.in

What you'll learn

Note:- This Course is not Applicable for 2025 Passing out Batch.Description: Welcome to our GATE (Graduate Aptitude Test in Engineering) class, where excellence meets opportunity! Are you ready to unlock the doors to prestigious institutes and lucrative career opportunities? Look no further, as our GATE class is tailored to equip you with the knowledge, skills, and confidence needed to ace this challenging examination. Led by experienced educators, including Mr. Pushpendra Kumar Pateriya, with over 5 years of dedicated GATE teaching experience, our class offers comprehensive coverage of the GATE syllabus. Whether you are aiming for a top rank or seeking admission to premier institutions for higher studies, our meticulously designed curriculum ensures that you are fully prepared for success. What sets our GATE class apart is our focus on conceptual clarity, problem-solving techniques, and strategic exam preparation. Through engaging lectures, interactive sessions, and regular assessments, we ensure that you not only grasp the fundamentals but also develop the proficiency to tackle complex problems with ease. Our class provides a supportive learning environment where doubts are addressed promptly, and individual progress is closely monitored. With personalized attention and guidance, we help you identify your strengths and weaknesses, allowing you to optimize your study plan and maximize your score potential. Join us on this transformative journey towards academic excellence and professional success. Whether you are a seasoned aspirant or just beginning your GATE preparation, our class is your stepping stone to a brighter future. Let's embark on this path together and make your GATE aspirations a reality! Learning Outcome of Course: 1. Comprehensive Understanding: Gain a thorough understanding of the entire GATE syllabus, covering all essential topics and concepts across multiple disciplines. 2. Conceptual Clarity: Develop a strong foundation in core concepts, theories, and principles, enabling you to solve problems with confidence and accuracy. 3. Problem-Solving Skills: Acquire effective problem-solving strategies and techniques, including time management and analytical reasoning, to tackle diverse and challenging questions encountered in the GATE exam. 4. Effective Study Strategies: Develop personalized study plans tailored to your strengths, weaknesses, and learning style, maximizing efficiency and optimizing preparation efforts. 5. Mock Test Performance: Enhance test-taking abilities through regular practice with simulated GATE exams, improving speed, accuracy, and adaptability to exam conditions. 6. Critical Analysis and Evaluation: Cultivate the ability to critically analyze questions, evaluate answer choices, and make informed decisions to maximize scores in the GATE exam. 7. Self-Assessment and Improvement: Engage in continuous self-assessment and feedback mechanisms to identify areas for improvement and implement targeted strategies for enhancement. 8. Confidence and Motivation: Build confidence in your abilities and stay motivated throughout the preparation journey, fostering a positive mindset conducive to success in the GATE examination. 9. Admission to Premier Institutions: Achieve a competitive GATE score that opens doors to admission in premier engineering institutes for postgraduate studies, paving the way for advanced academic and career opportunities.

  • Discrete Mathematics: Propositional and first order logic. Sets, relations, functions, partial orders and lattices. Monoids, Groups. Graphs: connectivity, matching, coloring. Combinatorics: counting, recurrence relations, generating functions. Linear Algebra: Matrices, determinants, system of linear equations, eigenvalues and eigenvectors, LU decomposition. Calculus: Limits, continuity and differentiability. Maxima and minima. Mean value theorem. Integration. Probability and Statistics: Random variables. Uniform, normal, exponential, poisson and binomial distributions. Mean, median, mode and standard deviation. Conditional probability and Bayes theorem. Computer Science and Information Technology
  • Boolean algebra. Combinational and sequential circuits. Minimization. Number representations and computer arithmetic (fixed and floating point).
  • Machine instructions and addressing modes. ALU, data-path and control unit. Instruction pipelining, pipeline hazards. Memory hierarchy: cache, main memory and secondary storage; I/O interface (interrupt and DMA mode).
  • Programming in C. Recursion. Arrays, stacks, queues, linked lists, trees, binary search trees, binary heaps, graphs.
  • Searching, sorting, hashing. Asymptotic worst case time and space complexity. Algorithm design techniques: greedy, dynamic programming and divide-and-conquer. Graph traversals, minimum spanning trees, shortest paths
  • Regular expressions and finite automata. Context-free grammars and push-down automata. Regular and contex-free languages, pumping lemma. Turing machines and undecidability.
  • Lexical analysis, parsing, syntax-directed translation. Runtime environments. Intermediate code generation. Local optimisation, Data flow analyses: constant propagation, liveness analysis, common sub expression elimination.
  • System calls, processes, threads, inter-process communication, concurrency and synchronization. Deadlock. CPU and I/O scheduling. Memory management and virtual memory. File systems.
  • ER-model. Relational model: relational algebra, tuple calculus, SQL. Integrity constraints, normal forms. File organization, indexing (e.g., B and B+ trees). Transactions and concurrency control.
  • Concept of layering: OSI and TCP/IP Protocol Stacks; Basics of packet, circuit and virtual circuit-switching; Data link layer: framing, error detection, Medium Access Control, Ethernet bridging; Routing protocols: shortest path, flooding, distance vector and link state routing; Fragmentation and IP addressing, IPv4, CIDR notation, Basics of IP support protocols (ARP, DHCP, ICMP), Network Address Translation (NAT); Transport layer: flow control and congestion control, UDP, TCP, sockets; Application layer protocols: DNS, SMTP, HTTP, FTP, Email

Avatar
Pushpendra Kumar Pateriya
Assistant Professor

Pushpendra Kumar Pateriya is an academician and administrator currently serving as the Head of the Department (HoD), School of Computer Science and Engineering, Lovely Professional University. With over a decade of experience in higher education, he has been actively involved in teaching, academic leadership, and curriculum development. He has qualified the Graduate Aptitude Test in Engineering (GATE) eight times, achieving a highest All India Rank (AIR) of 568, and is also UGC-NET qualified, reflecting his strong academic foundation and subject expertise. Since 2022, he has been actively mentoring students for the GATE examination and is currently handling his fifth batch of GATE preparatory classes. Under his guidance, students have achieved commendable results, including a highest AIR of 351 in Computer Science, demonstrating his effectiveness in competitive exam training. His areas of expertise include Operating Systems, Data Structures, Algorithms, and High-Performance Computing. He has contributed to faculty development programs and technical training initiatives, particularly in domains such as parallel computing, GPU acceleration, and emerging technologies. Pushpendra Pateriya is a strong advocate of outcome-based and industry-aligned education, emphasizing problem-solving, analytical thinking, and hands-on learning. He focuses on preparing students not only for academic excellence but also for competitive examinations and real-world technological challenges. With extensive experience in academic administration and student mentorship, he continues to work towards building a learning ecosystem that promotes innovation, research orientation, and practical skill development.


Avatar
Dr. Prince
Professor

Dr. Prince Singh is an academician currently serving as an Associate Professor at Lovely Professional University, with experience in teaching, research, and academic mentoring. He is actively involved in delivering quality education in the domain of Computer Science and Engineering, contributing to curriculum development and student-centric learning initiatives. His teaching approach emphasizes conceptual clarity, problem-solving, and practical application of knowledge, enabling students to build a strong academic foundation. Dr. Singh is committed to fostering an engaging learning environment through interactive pedagogy, peer learning, and outcome-based education practices. He continuously works towards enhancing students’ analytical thinking and technical skills, preparing them for both competitive examinations and industry requirements. With a focus on academic excellence and continuous improvement, he contributes to the development of a robust educational ecosystem that supports innovation, skill development, and research-oriented learning.