Innoskrit
AI-First Software Engineering Program

A Product-Building
Curriculum Journey

Students learn Java, DSA, Problem-Solving, Full Stack Engineering, AI, and System Design by repeatedly improving real systems. Filter by engineering year to see the right depth for your students.

300 Hours2 Portfolio Systems350+ DSA Problems
Filter by engineering year

Placement cells can pick the year they are planning for. The curriculum depth, hours, DSA problem count, and portfolio projects all adapt to the runway that year has left.

1st Year: Full foundations, patiently built, all the way to AI-powered systems.

300hours

Java, DSA, Full Stack, AI, and Design

2systems

Feature Flag System and Trello

350+problems

The complete A-to-Z DSA path

3year runway

Learn, Build, Add AI, Scale, and Launch

The project spine

Two products. One curriculum. AI added where it belongs.

We teach basics first, then use those basics to build real systems. Once the products are working, the AI course extends those same products with useful AI capabilities instead of disconnected demos.

Product build
Flags
Checkout redesign
AI board summary
Beta reports
Trello
Todo
Doing
Done
AI is added after the systems work: summaries, rule generation, risk analysis, semantic search, and human-reviewed suggestions.
Release safely

Feature Flag System

A LaunchDarkly-style platform for controlled product releases.

Students build a production-ready feature management platform where teams can create flags, target users, roll out features gradually, track changes, and safely turn functionality on or off without redeploying code.

JavaSpring BootPostgreSQLNext.jsWebSocketsAWS

Students build

  • Flag dashboard with projects, environments, owners, tags, and lifecycle states.
  • Rule engine for user segments, percentage rollouts, prerequisites, and kill switches.
  • Evaluation API that applications can call to decide whether a feature is enabled.
  • Audit logs, approvals, metrics, and release history for engineering teams.

AI extensions

  • Natural-language flag creation that converts release intent into targeting rules.
  • Rollout risk analyzer that explains blast radius before a launch.
  • Experiment and incident summarizer for product, engineering, and leadership updates.
A portfolio-grade backend-heavy SaaS product that proves API design, database modeling, auth, testing, observability, and product thinking.
Plan clearly

Trello

A collaborative kanban workspace for planning real engineering work.

Students build a Trello-inspired project management product with boards, lists, cards, members, comments, labels, activity timelines, and real-time collaboration, then evolve it into an AI-assisted planning system.

JavaSpring BootPostgreSQLNext.jsDrag and DropWebSockets

Students build

  • Boards, lists, cards, labels, due dates, attachments, comments, and member roles.
  • Drag-and-drop workflows with ordering, optimistic UI, and conflict handling.
  • Activity feeds, notifications, filters, search, and team permissions.
  • Reusable frontend components for dense product workflows.

AI extensions

  • Task breakdown assistant that converts a vague goal into cards, checklists, and owners.
  • Board summarizer that explains status, blockers, overdue work, and next actions.
  • Semantic card search and priority suggestions using embeddings and workspace context.
A collaboration product that demonstrates frontend depth, real-time systems, clean UX, access control, and AI features grounded in actual user workflows.
1st Year syllabus

The journey from fundamentals to AI-powered product systems.

Every module has clear outcomes, granular topic descriptions, problem-solving practice, and a project milestone tied back to the systems students are building.

01
Foundation25 Hours

Programming with Java

From syntax to backend-ready Java

Start with Java as the engineering language for the program. Students learn to write clean, testable code that later becomes the backend foundation for the Feature Flag System and Trello.

Module outcome

Students create small Java services and domain models that later become flags, users, boards, cards, and permissions.

Students can
  • Write clean Java programs with strong fundamentals.
  • Model real-world entities using OOP and SOLID basics.
  • Use collections, exceptions, files, streams, and tests confidently.

Java Fundamentals

Get comfortable with the language, tooling, debugging, and the mental model of writing programs that are easy to reason about.

Setup, IDE, Git, and Debugging

Install Java 17+, configure IntelliJ, run programs from the terminal, use breakpoints, inspect variables, and commit work cleanly.

Variables, Types, Operators, and Input

Understand primitive types, strings, casting, expressions, console input, and how type choices affect correctness.

Control Flow and Loops

Use conditionals, loops, switch expressions, guard clauses, and dry runs to translate requirements into working logic.

Methods and Recursion

Break code into reusable functions, reason about call stacks, and solve simple recursive problems before DSA begins.

Arrays, Strings, and Debug Tracing

Manipulate indexed data, trace loops, handle edge cases, and build confidence with the structures used heavily in DSA.

Object-Oriented Programming

Move from writing scripts to designing domain models for real products.

Classes, Objects, and Constructors

Represent products, users, permissions, cards, and flags as objects with meaningful state and behavior.

Encapsulation and Immutability

Protect state, expose safe APIs, and learn when immutable objects reduce bugs in product code.

Inheritance, Interfaces, and Polymorphism

Use abstractions for extensible behavior such as notification channels, flag rules, and card actions.

SOLID Principles Introduction

Apply single responsibility, dependency inversion, and open-closed thinking without over-engineering beginner code.

Collections and Generics

Learn the data containers used in backend services and problem solving.

List, Set, and Map

Choose the right collection for ordering, uniqueness, lookups, membership checks, and grouping.

ArrayList, LinkedList, HashSet, HashMap, and TreeMap

Compare behavior, performance, common operations, and real use cases in APIs and algorithms.

Generics and Type Safety

Design reusable containers, service responses, repositories, and utilities without losing compile-time safety.

Sorting and Comparators

Sort cards, releases, users, and problem inputs using custom ordering and comparator composition.

Errors, Files, Testing, and Modern Java

Round out the foundation with reliability habits that carry into every project.

Exception Handling

Use checked and unchecked exceptions, custom errors, and consistent failure messages for predictable APIs.

File Handling and Serialization

Read, write, parse, and persist simple data before moving to databases.

JUnit Basics and Testable Code

Write small unit tests, structure assertions, and catch regressions before code reaches larger systems.

Streams, Optional, Records, and Lambdas

Use modern Java features for transformations, null safety, DTOs, and concise business logic.

Concurrency Basics

Understand threads, executors, synchronization, and CompletableFuture at a practical backend level.

02
Problem Solving100 Hours

DSA and Problem Solving

The full A-to-Z sheet, built patiently

Walk the complete A-to-Z path from coding basics to graphs and dynamic programming. Since first-year students have a three-year runway, nothing is skipped: patterns, sorting, and fundamentals are built before the harder interview material.

Module outcome

Students reuse DSA thinking in product features such as rule evaluation, search, sorting, graph-like permissions, recommendations, and scheduling.

Students can
  • Solve 350+ curated problems spanning the entire A-to-Z path.
  • Master every core pattern from basics through graphs and DP.
  • Explain complexity, do dry runs, and turn unknown questions into familiar patterns.

Foundations, Sorting, and Bit Basics

Build raw coding fluency first: patterns, basic maths, hashing, every sorting algorithm, and the bit fundamentals that later-year tracks assume you already have.

Practice prompts
  • Pattern printing, Armstrong numbers, GCD/HCF, prime sieve
  • Selection, Bubble, Insertion, Merge, and Quick sort from scratch
  • Count digits, reverse a number, check palindrome, frequency hashing
Patterns and Basic Math

Translate logic into loops with pattern problems, then practice digit maths and number theory basics.

Count DigitsPalindrome NumberGCD of Two Numbers
Basic Recursion and Hashing

Reason about the call stack with simple recursion, then use hashing for counting and lookups.

Sum of First NFactorialFrequency of Elements
Sorting Algorithms

Implement and compare the classic sorts, understand stability, and reason about their complexity.

Merge SortQuick SortSort Colors (0s, 1s, 2s)
Bit Manipulation Basics

Set, clear, and toggle bits, count set bits, and use XOR tricks for single-number problems.

Count Set BitsSingle NumberPower of Two

Arrays and Binary Search

The two highest-frequency interview families: array manipulation from easy to hard, and binary search over both sorted data and answer spaces.

Practice prompts
  • Kadane's Maximum Subarray, Majority Element, Best Time to Buy and Sell Stock
  • Next Permutation, Merge Intervals, Set Matrix Zeroes, Rotate Image
  • Search in Rotated Sorted Array, Koko Eating Bananas, Median of Two Sorted Arrays
Easy and Medium Arrays

Traverse, mutate, and transform arrays in place with edge-case-driven single passes.

Two SumMajority Element IILongest Consecutive Sequence
Hard Arrays

Handle merges, inversions, and subarray problems that need careful invariants.

Merge IntervalsCount InversionsReverse Pairs
Binary Search on Arrays

Search sorted data and answer boundary questions like first and last position.

Search Insert PositionSingle Element in Sorted ArrayFind Peak Element
Binary Search on Answers

Recognize when to binary search over a value range instead of an index.

Koko Eating BananasAggressive CowsSplit Array Largest Sum

Strings and Linked Lists

Pointer discipline and character manipulation: from basic string handling to hard linked-list surgery.

Practice prompts
  • Reverse Words, Longest Palindromic Substring, Roman to Integer
  • Reverse Linked List, Detect Cycle, Merge Two Sorted Lists
  • Add Two Numbers, Reverse Nodes in K-Groups, Copy List with Random Pointer
Basic and Medium Strings

Use frequency maps, two pointers, and careful indexing on string problems.

Longest Common PrefixSort Characters by FrequencyLargest Odd Number in String
Singly and Doubly Linked Lists

Insert, delete, and traverse nodes across singly and doubly linked structures.

Middle of the Linked ListRemove Nth Node from EndDelete Node in DLL
Hard Linked List Patterns

Reverse in groups, rotate, flatten, and clone lists without losing pointers.

Reverse Nodes in K-GroupsRotate ListFlatten a Linked List

Recursion, Backtracking, and Bit Manipulation

Build choice trees, learn to prune search spaces, and pick up advanced bit tricks used in subset and XOR problems.

Practice prompts
  • Subsequences, Combination Sum I and II, Subset Sum
  • N-Queens, Sudoku Solver, Rat in a Maze, Word Search
  • Power Set, Single Number II and III, XOR of a range
Recursion Patterns

Generate subsequences and permutations, and reason about pick / not-pick choices.

Subsequence SumAll PermutationsString Palindrome Check
Backtracking

Track visited state, undo decisions, and prune impossible branches early.

N-QueensSudoku SolverPalindrome Partitioning
Advanced Bit Manipulation

Use bitmasks for subsets and solve tricky single-number and XOR-range questions.

Power SetSingle Number IIIXOR of Numbers in a Range

Stacks, Queues, Sliding Window, and Two Pointer

State-machine reasoning with stacks and queues, monotonic patterns, and the window techniques behind many medium and hard problems.

Practice prompts
  • Valid Parentheses, Min Stack, Next Greater Element
  • Largest Rectangle in Histogram, LRU Cache, LFU Cache
  • Longest Substring Without Repeating Characters, Minimum Window Substring
Stack and Queue Implementation

Implement stacks and queues in terms of each other and parse expressions.

Implement Stack using QueueInfix to PostfixValid Parentheses
Monotonic Stack

Solve previous / next greater problems and histogram-style questions.

Next Greater ElementTrapping Rain WaterSum of Subarray Minimums
Sliding Window and Two Pointer

Expand and shrink windows to answer substring and subarray questions in one pass.

Longest Substring with K DistinctFruit Into BasketsBinary Subarrays with Sum

Heaps, Greedy, Trees, BST, and Tries

Priority-based processing, greedy proofs, and the full tree family — binary trees, BSTs, and tries — used across interviews and product systems.

Practice prompts
  • Kth Largest Element, Merge K Sorted Lists, Task Scheduler
  • N Meetings in a Room, Job Sequencing, Fractional Knapsack
  • Level Order Traversal, Diameter, Lowest Common Ancestor, Vertical Order
  • Validate BST, Kth Smallest, Implement Trie, Maximum XOR
Heaps and Priority Queues

Handle top-k queries, streaming medians, and scheduling with heaps.

Kth Largest ElementMerge K Sorted ListsFind Median from Data Stream
Greedy Algorithms

Recognize when local choices are safe and communicate the proof clearly.

N Meetings in a RoomJob Sequencing ProblemCandy
Binary Trees

Traverse trees every way and solve structural problems like LCA and diameter.

Level Order TraversalDiameter of Binary TreeSerialize and Deserialize
BST and Tries

Use BST ordering for range and rank queries, and prefix trees for search.

Validate BSTKth Smallest in BSTImplement Trie

Graphs and Dynamic Programming

The two hardest and most decisive interview families, built from first principles: graph traversal and shortest paths, then DP across grids, subsequences, strings, and stocks.

Practice prompts
  • Number of Islands, Rotting Oranges, Course Schedule, Topological Sort
  • Dijkstra, Bellman-Ford, Floyd-Warshall, MST (Prim and Kruskal)
  • 0/1 Knapsack, Longest Increasing Subsequence, Edit Distance, Matrix Chain
  • DP on Stocks, DP on Subsequences, DP on Strings
Graph Traversals and Topological Sort

Represent graphs, traverse components, detect cycles, and order dependencies.

Number of IslandsCourse ScheduleWord Ladder
Shortest Paths and MST

Apply Dijkstra, Bellman-Ford, and minimum spanning tree algorithms to weighted graphs.

DijkstraCheapest Flights Within K StopsMinimum Spanning Tree
1D, 2D, and Grid DP

Model choices over indexes, capacities, and grids from brute force to tabulation.

House RobberUnique PathsMinimum Path Sum
DP on Subsequences, Strings, and Stocks

Define clean states for subsequence, matching, and stock problems.

Longest Increasing SubsequenceEdit DistanceBest Time to Buy and Sell Stock IV
03
Build Products85 Hours

Full Stack Product Engineering

Feature Flag System + Trello

Build the two core portfolio systems: a Feature Flag System and a Trello-style collaboration product. The goal is not toy CRUD, but real product architecture with auth, data modeling, testing, and deployment.

Module outcome

By the end of this module, students have both core systems working without AI. These become the base products for the AI module.

Students can
  • Build production-style APIs with Spring Boot and PostgreSQL.
  • Create polished Next.js product interfaces for dense workflows.
  • Ship two deployable systems with auth, tests, CI/CD, and cloud basics.

Spring Boot Backend

Design APIs that are organized, testable, secure, and ready for real product workflows.

Project Structure and Dependency Injection

Set up layered architecture with controllers, services, repositories, DTOs, validators, and configuration.

REST API Design

Design resources, status codes, pagination, filtering, versioning, and consistent error contracts.

Validation and Exception Handling

Protect the system with request validation, domain validation, global exception handlers, and useful error responses.

Testing with JUnit, Mockito, and Testcontainers

Write unit, integration, and repository tests around business rules, APIs, and database behavior.

Database and Domain Modeling

Turn product requirements into schemas that survive real usage and growth.

PostgreSQL Schema Design

Model users, workspaces, roles, flags, environments, boards, lists, cards, labels, and activity logs.

JPA and Hibernate

Use entities, relationships, transactions, projections, lazy loading, and query patterns safely.

Migrations with Flyway

Version database changes and manage schema evolution as the projects grow.

Indexes and Query Optimization

Add indexes for search, filters, rule evaluation, activity feeds, and board performance.

Authentication, Authorization, and Multi-Tenancy

Teach the product who the user is, what they can access, and which workspace they belong to.

JWT Authentication

Implement login, refresh tokens, secure password handling, and authenticated API flows.

Spring Security

Secure endpoints, configure filters, apply method-level permissions, and handle unauthorized access.

Role-Based Access Control

Model owners, admins, members, viewers, card assignees, and flag approvers.

Workspace Isolation

Prevent cross-tenant data leaks across organizations, projects, boards, and environments.

Next.js Frontend

Build product interfaces that feel useful, fast, and organized instead of demo-like.

React Fundamentals and Hooks

Build composable UI components for dashboards, forms, tables, drawers, cards, and activity feeds.

State Management and Data Fetching

Use local state, context, caching, optimistic updates, and error states for real workflows.

Forms and Validation

Create multi-step forms for flags, rollout rules, cards, checklists, labels, and permissions.

Drag and Drop Product UX

Build Trello-style board interactions with stable ordering, keyboard-friendly flows, and optimistic UI.

Realtime, Deployment, and Delivery

Move from local project to deployable system with collaboration and delivery discipline.

WebSockets and Live Updates

Broadcast card moves, comments, flag changes, rollout status, and collaboration activity.

Docker and Environment Config

Containerize frontend, backend, and database with local and cloud-ready configuration.

CI/CD with GitHub Actions

Run tests, builds, lint checks, and deployment steps consistently on every change.

AWS Basics

Deploy with EC2, RDS, S3, domains, HTTPS, environment variables, and basic monitoring.

04
Add AI60 Hours

AI Engineering for Product Systems

AI inside the same two systems

Learn AI basics first, then apply them only inside the Feature Flag System and Trello. Students do not build disconnected AI demos; they add AI capabilities to the products they already understand.

Module outcome

The same two products become AI-assisted systems: smarter releases, smarter planning, smarter search, and smarter summaries.

Students can
  • Use LLM APIs, prompting, embeddings, RAG, tools, and agent workflows.
  • Add AI features to the Feature Flag System and Trello with production guardrails.
  • Evaluate AI behavior for quality, cost, latency, and safety.

Python and LLM Foundations

Build enough AI engineering literacy to integrate models into software products responsibly.

Python for AI Workflows

Use Python functions, classes, modules, virtual environments, HTTP clients, async basics, and data processing.

How LLMs Work in Products

Understand tokens, context windows, temperature, latency, cost, streaming, and failure modes.

Model APIs and SDKs

Call LLM APIs, handle retries, stream responses, manage keys, and design clean service boundaries.

Structured Outputs

Force useful JSON responses for rule drafts, card creation, summaries, checklists, and risk reports.

Prompting, RAG, and Tool Use

Teach models to work with product context instead of giving generic chatbot answers.

Prompt Design and Evaluation

Write instructions, examples, rubrics, and regression checks for product-specific AI behavior.

Embeddings and Semantic Search

Index flag docs, release notes, incident history, cards, and comments for meaning-based retrieval.

RAG Pipelines

Retrieve relevant workspace context, ground model responses, cite sources, and reduce hallucination.

Function Calling and Tools

Let AI safely call product actions such as draft flag rule, create cards, summarize a board, or search history.

AI in the Feature Flag System

Add AI features that help teams launch software safely.

Natural-Language Flag Builder

Convert prompts like launch to beta users in Bengaluru at 10 percent into structured targeting rules.

Rollout Risk Analyzer

Use audience size, environment, dependencies, recent incidents, and usage metrics to explain release risk.

Experiment and Incident Summaries

Summarize flag history, metric changes, rollout events, comments, and actions into stakeholder-ready updates.

AI Guardrails for Releases

Add approval gates, confidence checks, auditability, and human review before AI-assisted launch changes.

AI in Trello

Add AI features that help teams plan, track, and explain work.

Task Breakdown Assistant

Turn a vague project goal into cards, checklists, labels, owners, and milestones using structured outputs.

Board and Sprint Summaries

Summarize done work, blockers, overdue tasks, stale cards, ownership gaps, and next actions.

Semantic Card Search

Find related cards and comments by meaning, even when users do not remember exact keywords.

Priority and Deadline Suggestions

Use due dates, labels, dependencies, and activity history to recommend what needs attention.

Production AI Systems

Make AI features shippable, observable, and safe enough for real users.

Tracing and Observability

Log prompts, retrieved context, model outputs, latency, cost, and user feedback for debugging.

Evaluation Suites

Create test cases for flag rules, card generation, summarization quality, and unsafe responses.

Cost and Latency Optimization

Choose models, cache outputs, stream responses, batch requests, and set fallbacks thoughtfully.

Human-in-the-Loop UX

Design AI suggestions as drafts users can inspect, edit, approve, reject, and audit.

05
Scale and Design30 Hours

Machine Coding and System Design

Design interviews from real products

Use the same product systems to learn low-level design, high-level design, scalability, queues, caching, and interview case studies. Students design systems they have actually built.

Module outcome

Students redesign Feature Flags and Trello for scale, reliability, multi-tenancy, realtime collaboration, and AI workloads.

Students can
  • Break vague requirements into clean classes, APIs, and workflows.
  • Design scalable architectures for collaboration, releases, search, and AI features.
  • Practice machine coding and system design interviews with stronger product intuition.

Machine Coding

Practice implementation-heavy design problems under interview constraints.

Problem Decomposition

Clarify requirements, identify entities, define APIs, plan data structures, and sequence implementation.

Parking LotSplitwiseBookMyShow
Clean Code and Extensibility

Write readable code with clear naming, small classes, low coupling, and test-friendly boundaries.

LLD Patterns in Product Features

Design flag rules, board actions, notification systems, rate limiters, and audit logs.

Feature Flag Rule EngineTrello Activity FeedRate Limiter
Timed Machine Coding Rounds

Practice scope control, incremental delivery, test cases, and final walkthroughs.

Design Patterns

Learn patterns through the two product systems instead of isolated textbook examples.

Strategy and Chain of Responsibility

Apply to targeting rules, notification routing, policy checks, and AI tool selection.

Factory, Builder, and Adapter

Create DTOs, model clients, card templates, flag templates, and provider integrations safely.

Observer and Command

Model activity feeds, undo/redo, audit logs, board events, and release events.

Repository and Service Boundaries

Keep business rules separate from persistence, APIs, and external services.

High-Level System Design

Scale the exact systems students have built, then generalize the patterns to interviews.

Scalability Fundamentals

Estimate traffic, storage, throughput, latency, read/write paths, and bottlenecks.

Caching and CDN Strategy

Cache flag evaluations, board metadata, search results, static assets, and AI outputs.

Queues and Event-Driven Architecture

Use async events for notifications, audit logs, AI summaries, indexing, and metrics ingestion.

Database Scaling

Compare indexes, partitioning, replication, sharding, read replicas, and denormalized views.

Reliability and Observability

Design health checks, alerts, tracing, retries, idempotency, and fallback behavior.

Interview Case Studies

Practice classic designs after building enough context to make answers concrete.

Practice prompts
  • Design Feature Flag Platform
  • Design Trello or Jira
  • Design URL Shortener
  • Design Instagram Feed
  • Design WhatsApp
  • Design Uber or Ola
Feature Flag Platform at Scale

Design low-latency evaluations, SDK caching, rule propagation, auditability, and kill switches.

Trello or Jira at Scale

Design boards, permissions, realtime updates, ordering, search, notifications, and collaboration.

AI Feature Architecture

Design RAG services, prompt stores, eval pipelines, vector search, and human approval flows.

Mock Design Interviews

Practice clarifying questions, diagrams, tradeoffs, bottlenecks, and final deep dives.

06
LaunchOngoing

Career Launchpad

Portfolio, interviews, and placement

Turn the journey into career outcomes with portfolio polishing, interview practice, resumes, LinkedIn, GitHub, referrals, and company-specific preparation.

Module outcome

Students convert their systems into case studies with architecture diagrams, demos, metrics, and interview stories.

Students can
  • Present the Feature Flag System, Trello, and AI extensions as strong portfolio work.
  • Practice coding, machine coding, system design, and behavioral interviews.
  • Build a credible job-search engine across resume, GitHub, LinkedIn, and referrals.

Portfolio Packaging

Make the projects easy for recruiters and interviewers to understand quickly.

Project READMEs and Case Studies

Document problem statement, architecture, features, tradeoffs, screenshots, setup, and demo links.

GitHub Hygiene

Clean commits, clear branches, issue tracking, tests, environment examples, and meaningful project boards.

Architecture Diagrams

Explain service boundaries, database design, auth, realtime updates, AI pipelines, and deployment.

Demo Storytelling

Practice a 3-minute and 10-minute walkthrough of both products and their AI capabilities.

Resume, LinkedIn, and Personal Brand

Translate learning into signals that hiring teams can trust.

Resume Reviews and Rewrites

Write project bullets with impact, technical depth, scale, ownership, and measurable outcomes.

LinkedIn Profile Optimization

Improve headline, about section, featured projects, proof of work, and recruiter search keywords.

GitHub Portfolio Positioning

Pin the strongest repositories and make technical depth visible before an interview starts.

Public Learning Posts

Turn project decisions, DSA learnings, and AI experiments into credible short posts.

Interview Preparation

Practice the rounds students will actually face.

Mock Coding Interviews

Run timed DSA rounds with feedback on approach, communication, code quality, and edge cases.

Machine Coding Interviews

Practice scoped product features, clean code, tests, and extensible design under time pressure.

System Design Interviews

Use Feature Flags, Trello, and classic systems to practice tradeoffs, scale, and reliability.

Behavioral Interview Prep

Use STAR stories from projects, teamwork, debugging, ownership, conflict, and learning moments.

Mentorship and Placement Support

Keep students accountable through the job search instead of stopping at course completion.

1:1 Mentor Reviews

Get guidance on project depth, interview readiness, applications, and weak areas.

Company-Specific Prep

Prepare for patterns, hiring rounds, and expectations at product companies and startups.

Referral Network Access

Use proof of work and mentor feedback to approach referrals with stronger credibility.

Offer and Negotiation Basics

Understand compensation conversations, timelines, competing offers, and professional communication.

Bring this curriculum to your campus.

We can walk you through the project journey, module structure, mentorship model, and how students graduate with interview practice plus serious portfolio systems.