Computer Science
Programming Fundamentals Challenges
Programming Fundamentals challenges put you inside the work of writing code that is correct, readable and fast. You'll build core skills in functions & data structures, object-oriented design and design patterns, work in Python or JavaScript, and learn to do code reading and refactoring the way teams expect.
From there you'll tackle the harder edges — algorithm analysis, complexity analysis, graph algorithms and generics & type systems — pushing into performance engineering, low-latency programming patterns and systems-language proficiency (Go, Rust, C++). Each challenge you solve earns a verified credential you can share with recruiters.
- PresentationBeginnerNew
Evaluate Intelligent Agents in a Sustainable-Logistics Simulation
Build a small grid-world simulation where a delivery agent must complete 10 stops while respecting traffic, charging needs, and time windows. Implement three classical agent des…
- Intelligent Agents
- Simulation Design
- Python
Introduction to Artificial Intelligence - AnalysisSeniorNew
Backtest a Gilt-Versus-Corporate-Bond Spread Strategy
Using the supplied two-year daily market-history dataset of gilt and corporate-bond yields, prices, and bid-ask spreads, design and backtest a long-short relative value strategy…
- Fixed Income Arbitrage
- Yield Spread Analysis
- Backtesting
Open coursework - AnalysisBeginnerNew
Approximate Inference for a Topic Model on Customer Tickets
You receive 180,000 tickets (subject + body) spanning the last 18 months. Preprocess into a bag-of-words representation with sensible stopwords and bigrams. Fit a 20-topic LDA v…
- Variational Inference
- Latent Dirichlet Allocation
- Approximate Inference
Open coursework - CodeBeginnerNew
Tabular Q-Learning for Warehouse Slotting
You receive a Python discrete-event simulator with state encoded as a 12-dimensional categorical vector (around 8,000 reachable states) and 6 possible slotting actions, plus 2 y…
- Tabular Rl
- Q Learning
- Epsilon Greedy
Open coursework Practice your coursework on real scenarios.
Every challenge is shaped from real-world context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- AnalysisIntermediateNew
Choose the Right Tenant Containment Strategy for an Edge Platform
Working only from the provided materials, reach and defend a containment recommendation. Read the documented incident record (case-file) to understand what triggered the review …
- Containment
- Virtualization
- Wasm
Open coursework - CodeBeginnerNew
Implement a Distance-Vector Routing Algorithm
Implement distance-vector routing in Python: each simulated router maintains a distance vector, exchanges vectors with neighbors every 1 second of simulated time, and updates it…
- Routing
- Distance Vector
- Network Simulation
Open coursework - AnalysisIntermediateNew
Benchmark Approximate Nearest-Neighbor Indexes for a Code-Search Startup
You receive a 5 M-vector sample (768-dim, float32) and a 1,000-query labeled benchmark with ground-truth top-50 neighbors per query. Index the same sample in Chroma (HNSW), Qdra…
- Ann Indexes
- Hnsw
- Benchmarking
Vector Databases and Embeddings - CodeFoundationalNew
Classify Retail Product Photos for an E-Commerce Marketplace
Use a publicly-available product-image dataset (e.g., Fashion-MNIST extended, or a Kaggle e-commerce subset of around 10k images across 12 categories). Fine-tune a small pretrai…
- Image Classification
- Transfer Learning
- Pytorch
Open coursework - Browse challenges
Explore role
Marketing Analyst
Plan and measure campaigns that grow the business. Funnel analytics, attribution, segmentation, and the rigorous measurement that lets marketing defend its budget at the leadership table.
- StrategyBeginnerNew
IDE-Assisted Refactoring Bootcamp for a Junior Backend Team
Design a 5-day curriculum centered on 10 katas chosen for refactoring-pattern coverage (e.g., Gilded Rose for replace-conditional-with-polymorphism, Tennis kata for extract-meth…
- Refactoring
- Katas
- Ide Tooling
Refactoring and Code Smell Detection - CodeIntermediateNew
Refactor a Big-Ball-of-Mud Java Servlet Application
Week 1: install JUnit 5 + Testcontainers harness, write characterization tests for the 2 target workflows (PolicyIssue + ClaimSubmit) reaching at least 80 percent branch coverag…
- Refactoring
- Characterization Testing
- Legacy Systems
Software Evolution and Maintenance - CodeIntermediateNew
Teach a Warehouse Cobot from Operator Demonstrations
You receive a simulated UR5e cobot in PyBullet, plus 12 example demonstrations of two kitting sequences. Implement Dynamic Movement Primitives (DMPs — a classic LfD technique th…
- Learning From Demonstration
- Dynamic Movement Primitives
- Human Robot Interaction
Human-Robot Interaction - CodeIntermediateNew
Run a Monte Carlo Tree Search Strategy for a Robotics Pick-and-Place Task
You receive a simulator of the pick-and-place task: a bin with 10 randomly-placed parts, an action space of which part to pick next, and a reward = parts picked per minute with …
- Monte Carlo Tree Search
- Planning
- Simulation
Open coursework Build a verifiable portfolio.
Submissions become evidence. Reviewers with shipping experience score against a rubric; the result becomes a credential anyone can verify.
Why Ewance
- CodeBeginnerNew
Compare MDP Solvers for a Smart-Grid Battery Dispatch Pilot
Model home-battery dispatch as a finite MDP: state is (state-of-charge, hour-of-day, current price tier), actions are charge/hold/discharge with realistic efficiency losses, tra…
- Markov Decision Processes
- Value Iteration
- Policy Iteration
Artificial Intelligence: Principles and Techniques - AnalysisBeginnerNew
Spectral Clustering for an Urban-Mobility Operator's Network
You receive 6 months of anonymized O-D trip data (around 4 million trips, around 8,000 virtual stations), the current 9 hand-drawn zones, and the operations team's KPIs (rebalan…
- Spectral Methods
- Spectral Clustering
- Graph Laplacian
Machine Learning on Graphs - AnalysisBeginnerNew
Topic Modeling for Sustainable Fashion Brand's Social Media
You are given a dataset of 50,000 social media posts (text only) mentioning EcoWear. Your task is to preprocess the text, apply an unsupervised topic modeling technique (e.g., L…
- Topic Modeling
- Text Mining
- Lda
Open coursework - CodeIntermediateNew
Code Review and Refactoring of a Legacy E-Commerce Module
You are given a codebase (Java/Spring Boot) of the order module. Perform a static analysis, document issues (e.g., god classes, tight coupling), and write a refactoring proposal…
- Code Review
- Refactoring
- Java
Open coursework - CodeFoundationalNew
Build a Simple Neural Network to Read Handwritten Postal Codes
You receive a labeled dataset of about 60,000 handwritten digit images (28x28 grayscale) drawn from Indian postal forms. Build two models from scratch in PyTorch: (1) a 2-layer …
- Neural Networks
- Convolutional Neural Networks
- Pytorch
Open coursework - CodeIntermediateNew
Plan Warehouse Pick Routes with a Classical Planner
You receive a stylized warehouse map (aisle graph), 30 sample shifts of pick tasks, and the current heuristic's outputs. Write a PDDL domain + problem generator, solve with at l…
- Pddl Modeling
- State Space Search
- Classical Planning
Open coursework - CodeIntermediateNew
Semantic Parser for an Enterprise Analytics Assistant
Define a small typed query language (filter, aggregate, group_by, time_range, metric). Curate or write 200 training examples covering the controlled subset and 50 held-out test …
- Semantic Parsing
- Grammar Design
- Transformer Models
Computational Semantics - CodeIntermediateNew
Integer Programming for Cloud Resource Allocation
Your task is to formulate an integer programming model to select the number of reserved instances (each type: compute, memory, storage) and allocate on-demand instances monthly.…
- Integer Programming
- Python
- Pulp
Operations Research and Optimization - CodeIntermediateNew
Forecasting Model for Online-Game Daily Active Users
Build forecasts at 14-day horizon per region using: (1) classical baseline — SARIMA or Prophet; (2) ML approach — gradient-boosted regressor on engineered features (day-of-week,…
- Supervised Learning
- Time Series Forecasting
- Python Programming
Machine Learning (CS Elective) - DesignBeginnerNew
Build a Multi-Criteria Vendor Selection Tool for an AI Consulting Firm
You will design a Multi-Criteria Decision Analysis (MCDA, a structured way to score options against weighted criteria) tool that accepts 6-10 vendor options, 6-12 weighted crite…
- Mcda
- Decision Support Systems
- Streamlit
Open coursework - CodeIntermediateNew
Forecast Intraday FX Volatility for a London Liquidity Desk
You receive 18 months of tick-level mid-quote data for six FX pairs plus a calendar of scheduled macro events. Resample to 1-minute bars, engineer realized-volatility features, …
- Time Series Forecasting
- Feature Engineering
- Model Validation
Open coursework - CodeBeginnerNew
Image Search for a DTC Furniture Retailer's App
Use a pretrained vision-embedding model (CLIP ViT-B/32 or DINOv2-small). Index a catalog of around 1,500 furniture images. Curate a small evaluation set of around 50 user-style …
- Image Embeddings
- Vision Transformers
- Image Search
Open coursework
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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