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.
- CodeSeniorNew
Min-Cost Max-Flow for Cloud Workload Placement
Receive 30 days of anonymized placement requests (workload CPU/memory shape, affinity rules), zone capacity per day, and cross-zone bandwidth costs. Model the placement as a min…
- Network Flows
- Algorithm Analysis
- Graph Algorithms
Advanced Algorithms - CodeIntermediateNew
Natural Language Inference for an HR-AI Compliance Tool
Use SNLI/MNLI/ANLI as starting data and curate 200 domain-specific HR examples (synthetic or anonymized) for fine-tuning. Fine-tune a small encoder (DeBERTa-v3-base or similar),…
- Natural Language Inference
- Transformer Models
- Fine Tuning
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 - AnalysisBeginnerNew
Model Diffusion of a Hashtag Across a Music-Discovery Platform
You receive 30 days of hashtag-usage data (about 2.4 million events) with account metadata and the follow graph between active hashtag users. Fit an information-diffusion model …
- Diffusion Models
- Network Analysis
- Causal Attribution
Social Network Analysis and Web Science Develop in-demand professional skills.
Each challenge names the skills it strengthens. Over time, your profile fills with the competences a hiring manager would actually look for.
Why Ewance
- CodeBeginnerNew
Prototype a Multimodal Visual-Question-Answering Demo
You will use a small open-source vision-language model (e.g., LLaVA-1.5-7B or PaliGemma) and prompt-engineer it for the warehouse-VQA task. Build a Gradio web demo. Construct a …
- Vision Language Models
- Multimodal Perception
- Prompt Engineering
Open coursework - ResearchSeniorNew
SAT-Based Planner for Smart-Grid Demand Response
Encode the dispatch problem (which customers to curtail by how much, respecting per-customer contractual caps and grid-cell totals) as a SAT or MaxSAT instance. Solve 50 histori…
- Sat Based Planning
- Constraint Encoding
- Benchmarking
Automated Planning - 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 - AnalysisIntermediateNew
Exploration Strategies for a Recommendation Bandit
You receive 60 days of anonymized impression/click logs covering around 200 content items and user features (cohort, listening history bucket). Build a contextual-bandit simulat…
- Contextual Bandits
- Thompson Sampling
- Ucb
Reinforcement Learning - Browse challenges
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Pricing Strategist
Set the price that captures value without leaving sales on the table. Demand modelling, willingness-to-pay research, and the disciplined experimentation that turns pricing into a competitive advantage.
- AnalysisBeginnerNew
Build a Topic-Modeling Pipeline for Citizen Feedback
Take the 60,000 comments (anonymized). Build a BERTopic pipeline with multilingual sentence embeddings (Catalan + Spanish + occasional English). Tune number-of-topics via topic-…
- Topic Modeling
- Bertopic
- Multilingual NLP
Open coursework - CodeBeginnerNew
Build a Face-Anonymization Tool for a Civic-Tech Newsroom
Use a pretrained face detector (RetinaFace or YOLOv8-face is fine). Build a Python tool with a Gradio or Streamlit UI that: (1) detects faces in an uploaded photo, (2) shows det…
- Object Detection
- Image Processing
- Opencv
Open coursework - 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
Refit a Pricing Model for an Insurance Comparison Site
You receive 9 months of quote-impression data (about 14 million events) with about 60 features and click labels. Refit logistic regression with elastic-net regularization plus a…
- Regularized Regression
- Feature Interactions
- Calibration
Statistical Machine Learning Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- 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
Computer Vision (Undergraduate) - 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
AI and Quantitative Finance - CodeIntermediateNew
AI-Driven Sales Lead Scoring for a B2B SaaS Scale-Up
You will receive a sample dataset of 200 leads with fields like company size, industry, email open rates, and website visits. Using AI tools, you must craft prompts to generate …
- Prompt Engineering
- Lead Scoring
- Data Analysis
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 - CodeFoundationalNew
Optimizing Inventory for a Barcelona D2C Cosmetics Brand
You are given a CSV file with 6 months of daily sales data for 20 SKUs, including product name, date, units sold, and current stock level. Your task is to write a Python program…
- Python
- Data Cleaning
- Data Analysis
Open coursework - CodeIntermediateNew
Build a Real-Time Streaming Pipeline for Card-Fraud Scoring
Using the provided transaction-event sample, the cardholder feature snapshot, the reference scoring service, and the risk team's experiment specification, build a stream-process…
- Stream Processing
- Kafka
- Flink
Open coursework - AnalysisIntermediateNew
Vehicle-to-Everything (V2X) Communication Trial Analysis
Load the anonymised dataset (logged packet RX/TX, PC5 sidelink RSSI, RSRP, SINR, vehicle trajectory, application latency for safety messages). Compute the canonical 3GPP Release…
- C V2x
- Pc5 Sidelink
- Wireless Performance Analysis
Wireless and Mobile Networks - CodeIntermediateNew
Build a Feature Store Backbone for a Healthtech ML Team
You receive synthetic wearable telemetry (heart rate, accelerometer, sleep stages) for around 5,000 patients across 90 days, plus the existing scattered feature scripts from the…
- Feature Engineering
- Data Modeling
- Python
Data Engineering and Big Data Systems - AnalysisBeginnerNew
Build a Public Open-Data Dashboard for Urban Mobility
Pull the city's open-data cyclist-collision dataset (10 years of incidents, geocoded). Define a clear before/after window around the protected-lane rollout, control for traffic-…
- Exploratory Data Analysis
- Data Wrangling
- Geospatial Analysis
Applied Data Analysis and Practical Data Science - ResearchSeniorNew
Probabilistic Numerics for an ODE-Constrained Battery Model
You receive 12 months of charge/discharge cycle data for 50 battery packs from a delivery-van fleet, plus the existing single-particle ODE degradation model (Python). Use a prob…
- Probabilistic Numerics
- Bayesian Inference
- Ode Modeling
Probabilistic Machine Learning - DesignIntermediateNew
Visualize Embedding Drift for a RAG Knowledge Assistant
You receive weekly snapshots over 12 weeks of around 50,000 document embeddings each (1024-dim). Design and build a visualization tool that: (a) projects each snapshot to 2D wit…
- Embeddings
- Dimensionality Reduction
- Umap
Open coursework - CodeBeginnerNew
Fuzzy-Logic Controller for a Sustainable-Greenhouse Operator
You receive a year of 15-minute climate logs (inside/outside temperature, humidity, light, CO2), the current rule-based controller, and the head grower's qualitative description…
- Fuzzy Logic
- Mamdani Inference
- Rule Based Systems
Fuzzy Logic, Knowledge Representation, and Symbolic Reasoning
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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