Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal

India · AICTE flexible curricula

Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal

36 lab practicals for the RGPV syllabus.

RGPV Bhopal’s B.Tech CSE on the AICTE flexible curricula, including the Programming Practices labs in Java and Python. Every lesson is stepped, compiled and checked by a real toolchain on your own machine — the model reviews your code afterwards, it does not decide whether you passed.

Download GroutCodeAll syllabuses

Updated

Semester by semester

Programme: B.Tech Computer Science and Engineering. Scheme: AICTE Flexible Curricula (grading system). Open a course to see its practical units and the lab lesson GroutCode ships for each.

  1. Semester 2

    1 course3 lab lessonsC++
    • BT205C++

      Basic Computer Engineering

      3

      lessons

      • Algorithms in C++: operators, loops, arrays, searching and an expression evaluator
      • Classes in C++: a Fraction type, a shape hierarchy and a growable stack
      See all 3 lessons
      1. 1Algorithms in C++: operators, loops, arrays, searching and an expression evaluatorUnit II · Algorithms, Programming Paradigms and Introduction to C++
      2. 2Classes in C++: a Fraction type, a shape hierarchy and a growable stackUnit III · Objects, Classes and Inheritance in C++
      3. 3C++ lab: expressions, classes, overloading, inheritance, stack, queue and linked listUnit LAB · List of Experiments

  2. Semester 3

    2 courses10 lab lessonsCJava
    • CS303C

      Data Structure

      5

      lessons

      • Arrays, linked lists and a polynomial ADT in C
      • Stacks, queues and their applications in C
      See all 5 lessons
      1. 1Arrays, linked lists and a polynomial ADT in CUnit I · Introduction to Data Structures, Arrays and Linked Lists
      2. 2Stacks, queues and their applications in CUnit II · Stacks and Queues
      3. 3Binary search trees, AVL balancing and a min-heap in CUnit III · Trees
      4. 4Graphs in C — traversals, topological order, Kruskal, Prim and DijkstraUnit IV · Graphs
      5. 5Seven sorts, two searches and a linear-probing hash table in CUnit V · Sorting, Searching and Hashing
    • CS305Java

      Object Oriented Programming & Methodology

      5

      lessons

      • From procedural functions to a Student object model, with text IO in Java
      • An encapsulated bank account in Java — state, static members, message passing and closing
      See all 5 lessons
      1. 1From procedural functions to a Student object model, with text IO in JavaUnit I · Introduction to Object Oriented Thinking & Object Oriented Programming
      2. 2An encapsulated bank account in Java — state, static members, message passing and closingUnit II · Encapsulation and Data Abstraction
      3. 3A college department in Java — inheritance, interfaces, association and aggregationUnit III · Relationships
      4. 4A payments checkout in Java — overloading, overriding and run-time dispatchUnit IV · Polymorphism
      5. 5ATM and library case studies in Java — strings, exceptions, threads and collectionsUnit V · Strings, Exception Handling, Multi-threading and Collections

  3. Semester 4

    4 courses18 lab lessonsCJavaPython
    • CS402C

      Analysis Design of Algorithm

      6

      lessons

      • Binary search to Strassen — divide and conquer, measured
      • Greedy algorithms — merge patterns, Huffman, knapsack, jobs, MST and Dijkstra
      See all 6 lessons
      1. 1Binary search to Strassen — divide and conquer, measuredUnit I · Algorithm Analysis and Divide and Conquer
      2. 2Greedy algorithms — merge patterns, Huffman, knapsack, jobs, MST and DijkstraUnit II · Greedy Strategy
      3. 3Dynamic programming — knapsack, multistage graphs, reliability design and Floyd-WarshallUnit III · Dynamic Programming
      4. 4Backtracking and branch & bound — n-queens, graph colouring, Hamiltonian cycles and TSPUnit IV · Backtracking and Branch & Bound
      5. 5Trees and graph traversal — BST, AVL balancing, BFS and DFSUnit V · Trees, Graph Traversal and NP-Completeness
      6. 6ADA lab — searching, sorting, Strassen, greedy, MST, shortest paths, TSP and Hamiltonian cyclesUnit LAB · List of Experiments
    • CS405C

      Operating Systems

      1

      lesson

      • OS lab — CPU scheduling, semaphores, page replacement, disk scheduling and the banker's algorithm
      See the units
      1. 1OS lab — CPU scheduling, semaphores, page replacement, disk scheduling and the banker's algorithmUnit LAB · List of Experiments
    • CS406AJava

      Programming Practices (a) (Java)

      4

      lessons

      • Java fundamentals — casting, control flow, an Account class and a Shape hierarchy
      • Linked structures, generics and the Collections Framework
      See all 4 lessons
      1. 1Java fundamentals — casting, control flow, an Account class and a Shape hierarchyUnit I · Basic Java Features
      2. 2Linked structures, generics and the Collections FrameworkUnit II · Java Collections Framework
      3. 3Threads, monitors and URLs — from a thread's life cycle to a deadlock-free bankUnit III · Advance Java Features
      4. 4The Java lab list as one library system — scope to multithreadingUnit LAB · List of Programs
    • CS406CPython

      Programming Practices (c) Python

      7

      lessons

      • Python basics — literals, strings, operators and a precedence-correct calculator
      • Python data structures — lists, tuples, dictionaries and sets at work
      See all 7 lessons
      1. 1Python basics — literals, strings, operators and a precedence-correct calculatorUnit I · Introduction
      2. 2Python data structures — lists, tuples, dictionaries and sets at workUnit II · Data Structure
      3. 3Python control flow — decisions, loops, break, continue and passUnit III · Control Flow
      4. 4Python OOP — a bank account hierarchy and an operator-overloading VectorUnit IV · Object oriented programming
      5. 5Python exceptions — try, except, else, finally and your own error classesUnit V · Exception
      6. 6Python modules and packages — building, importing and inspecting them by handUnit VI · Modules and Packages
      7. 7A log-processing toolkit from Python's standard libraryUnit VII · Standard Libraries

  4. Semester 5

    3 courses4 lab lessonsCSQLPython
    • CS501C

      Theory of Computation

      1

      lesson

      • Automata in C: DFAs, Mealy-style converters, subset construction, two PDAs and a Turing machine
      See the units
      1. 1Automata in C: DFAs, Mealy-style converters, subset construction, two PDAs and a Turing machineUnit LAB · List of Experiments
    • CS502SQL

      Database Management Systems

      2

      lessons

      • Relational algebra in SQL: selection to division, constraints, indexes and triggers
      • The DBMS lab list on the emp table: duplicates, alternate rows, Nth salary, savepoints and rule triggers
      See the units
      1. 1Relational algebra in SQL: selection to division, constraints, indexes and triggersUnit II · Relational Data Models and Query Languages
      2. 2The DBMS lab list on the emp table: duplicates, alternate rows, Nth salary, savepoints and rule triggersUnit LAB · Lab Assignments
    • CS506Python

      Python (LAB)

      1

      lesson

      • The Python lab list: GCD, Newton's root, searching, three sorts, primes, matrices and a word counter
      See the units
      1. 1The Python lab list: GCD, Newton's root, searching, three sorts, primes, matrices and a word counterUnit LAB · List of Experiments

  5. Semester 6

    1 course1 lab lessonC
    • CS602C

      Computer Networks

      1

      lesson

      • Error control, framing and routing — the CN lab programs in C
      See the units
      1. 1Error control, framing and routing — the CN lab programs in CUnit LAB · List of Experiments

The full 43-course syllabus is transcribed in the app, including the theory courses. Lessons are authored against the course codes that have practical work, and the list grows with each release.

GroutCode is not affiliated with or endorsed by Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal. Course codes and titles are transcribed from the institution’s published scheme documents.

How a practical runs

The same five steps for every lesson, in every language.

  1. 1

    Pick your syllabus

    Choose your university or board and the semester or class you are in. The course list is the transcribed official scheme, not an approximation.

  2. 2

    Open a lab lesson

    Each lesson is a stepped practical for a specific course, with a starter file you edit and a test file you do not.

  3. 3

    Write the code yourself

    The starter has the signatures and the TODOs. You implement them in the editor, in the language your course actually uses.

  4. 4

    Run the checks

    The toolchain compiles and runs the tests — 8 to 15 of them across the lesson, one per step, so you find out which change broke what.

  5. 5

    Get the review

    Once the tests pass, the model reads your implementation and tells you the input that breaks it. It never reports the pass or fail itself.

Why the compiler grades, not the model

The obvious way to build an AI lab tool is to let the model read the student’s code and say whether it is correct. It is also the way that produces a tool nobody can trust. A model will tell you your code works when the compiler says otherwise, and it will fail you for a style it happens to dislike.

So the two jobs are split:

  • The model designs the lesson, writes the starter and the tests, and — after the tests pass — reads what you actually wrote and tells you the input that breaks it.
  • The toolchain decides whether it compiles and whether each step passes. That verdict is not negotiable and the model never issues it.

And why steps instead of one big task

A 40-to-60 minute practical with a single Run at the end gives a beginner one bit of feedback an hour, and it arrives after every decision has already been made. Each lesson here is 8 to 15 steps, each with its own instruction and its own check, so you find out which change broke what while you still remember making it.

Frequently asked questions

Does GroutCode cover the RGPV AICTE flexible curricula?

Yes. GroutCode ships the transcribed RGPV AICTE flexible curricula for B.Tech Computer Science and Engineering — 43 courses — with 36 authored lab lessons mapped to specific course codes. The syllabus was transcribed from the official documents, and the source and checksum of each one is recorded in the app.

Which languages do the RGPV practicals use?

C (14 lessons), Java (9 lessons), Python (8 lessons), C++ (3 lessons), SQL (2 lessons). The language is set per course code rather than guessed from the title, because the same subject is taught in different languages at different institutions.

Does the AI just write the practical for me?

No. The starter file has the signatures and the TODOs; you implement them. The toolchain — not the model — decides whether your code compiles and whether each step passes, so the AI cannot tell you your code works when the compiler disagrees. What it does afterwards is read your implementation and point out the input that breaks it.

Do the practicals work offline?

The lessons, the syllabus and the test runner are bundled in the app and run locally, so the compile-and-check loop works with no connection. The review step at the end uses a model, which can be a local one or a cloud one with your own key.

What do I need installed?

GroutCode detects which toolchains are present on your machine and tells you what is missing and what would fix it. You need the compiler or interpreter for the language your course uses — a C compiler, a JDK, Python, Node or SQLite.

Other syllabuses

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KTU

APJ Abdul Kalam Technological University

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85

lab lessons

2024 schemeC · Java · Node.js · Python
Visvesvaraya Technological University

VTU

Visvesvaraya Technological University

Karnataka’s 2022 scheme across CSE, ISE, AI-ML, AI-DS and ECE, including the dedicated lab courses.

123

lab lessons

2022 schemeC · Python · Java · C++
Anna University, Chennai

Anna University

Anna University, Chennai

Anna University’s Regulations 2021 B.E. CSE, from Python and C programming to the data structures and OOP laboratories.

31

lab lessons

R2021C · Python · Java · SQL

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