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.
- ResearchIntermediateNew
Compare Kernel Methods to Trees on a Genomics Classification Task
You receive a curated benchmark of about 12,000 labeled variants with ~120 numerical + ~40 string features. Fit kernel SVMs (RBF, polynomial, string), random forest, and XGBoost…
- Kernel Methods
- Svm
- Tree Ensembles
Open coursework - CodeBeginnerNew
GPU Cost Dashboard for an AI Consulting Practice
Pull AWS Cost and Usage Report, GCP billing export, and Lambda Labs invoices into a single Parquet table. Implement a tagging convention (project + client + experiment_id) and a…
- Cloud Cost Attribution
- Etl Pipelines
- Data Modeling
Cloud Computing for Data and ML - CodeIntermediateNew
Implement and Tune HyperLogLog for Trace-Stream Cardinality in Go
Working from the HyperLogLog paper (provided as a real source) and the provided representative trace sample, implement HyperLogLog from scratch in Go with no third-party algorit…
- Randomized Algorithms
- Sketching
- Algorithm Analysis
Open coursework - 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 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
- CodeIntermediateNew
Build a Vector-Search Backend for an Enterprise AI Knowledge Assistant
You receive a corpus of around 20,000 PDFs (mixed scanned and digital) totalling around 30 GB and a labeled retrieval set of 200 queries with human-judged ground-truth passages.…
- RAG
- Vector Search
- Embeddings
Data Engineering and Big Data Systems - CodeIntermediateNew
Edge-Inference Pipeline for a Smart-Factory Vibration Monitor
Architect a pipeline that runs on an ESP32-S3 + STM32 combo (provided): (1) sample 3-axis accelerometer at 3.2 kHz, (2) compute windowed FFT features on-device every 1s, (3) run…
- Edge Computing
- Embedded Systems
- Sensors And Actuators
Internet of Things and Cyber-Physical Systems - DesignSeniorNew
OTA Firmware-Update Architecture for a 50,000-Device Smart-Meter Fleet
Design a 4-stage OTA architecture: (1) signed image build + manifest, (2) backend rollout (1 percent canary, 10 percent expand, 50 percent expand, 100 percent), (3) device-side …
- Embedded Systems
- Cyber Physical Systems
- Edge Computing
Internet of Things and Cyber-Physical Systems - CodeIntermediateNew
MinHash Similarity Sketch for a Job-Board Deduplication Pipeline
Implement a MinHash signature generator (128 permutations) over shingled job-posting text (5-gram word shingles). Build an LSH banding index (16 bands of 8 hashes each) tuned fo…
- Minhash
- Locality Sensitive Hashing
- Probabilistic Data Structures
Randomized Algorithms - 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.
- CodeSeniorNew
Port a Numerical Kernel from CPU to GPU for a CFD Simulator
Receive the existing CFD solver (C++17 + OpenMP, around 8,000 lines, the hot kernel is a 7-point stencil sweep over a 512^3 grid), the validation harness, and access to an A100 …
- Gpu Programming
- Cuda
- Parallelism
Open coursework - CodeBeginnerNew
Reason about Drone Mission Plans with Probabilistic Logic
Build a small Bayesian network (around 12 nodes) capturing weather, no-fly-zone proximity, battery state, operator certification, and mission risk. Implement exact inference (va…
- Bayesian Networks
- Probabilistic Inference
- Knowledge Representation
Introduction to Artificial Intelligence - CodeBeginnerNew
Build an Embedding-Based Semantic Search for a Legal-Document Corpus
Embed the 380k-document corpus using a multilingual sentence-transformer (e.g. multilingual MPNet or LaBSE). Store embeddings in FAISS or pgvector. Build a search service that r…
- Deep Learning
- Ml Applications
- Python Programming
Machine Learning (CS Elective) - CodeIntermediateNew
Design a Force-Controlled Polishing Skill for a Watchmaker
You receive simulated polishing trajectories from the manufacturer's robot, force-sensor logs from 20 master-craftsman demonstrations, and a quality-rubric (mirror finish 1-5) f…
- Impedance Control
- Force Control
- Manipulation
Robotics 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
- CodeFoundationalNew
Parallelize an Image-Processing Pipeline with Data Parallelism
Your analysis task is to take the serial pipeline module and its configuration (provided as 'serial-pipeline-module'), run it against the representative image batch described in…
- Data Parallelism
- Python
- Multiprocessing
Open coursework - 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
Detect Fraudulent Refund Requests for a Mid-Market Marketplace
You receive a labeled dataset with buyer history, seller history, shipping carrier, refund reason text, and outcome label (legit / fraud). Train and evaluate at least two classi…
- Classification
- Model Calibration
- Imbalanced Classification
Open coursework - AnalysisBeginnerNew
Interpretable-by-Design GAM for an Insurer's Claims Triage
You receive an anonymized claims dataset (around 60,000 claims, target: log reserve), a feature schema (22 features), and an existing LightGBM baseline (held-out R^2 of 0.78). T…
- Generalized Additive Models
- Ebm
- Interpretability
Explainable and Interpretable AI - 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 - CodeSeniorNew
Coordinate a Fleet of Warehouse Robots
Implement a simulated warehouse grid with 80 robots solving a pick-and-deliver workload. Design a decentralized coordination protocol (recommend a contract-net or auction-based …
- Multi Agent Coordination
- Decentralized Algorithms
- Simulation
Open coursework - AnalysisBeginnerNew
Audit a Climate-Tech Sensor Dataset for Production Readiness
You receive 18 months of raw sensor readings from 1,200 sensors (about 800M rows), plus a sensor-metadata table (location, firmware version, deployment date). Profile the data f…
- Data Quality Audit
- Data Profiling
- Time Series Analysis
Applied Data Analysis and Practical Data Science - AnalysisFoundationalNew
Sentiment Analysis for Tel Aviv D2C Cosmetics Brand
You are provided with a dataset of 10,000 customer reviews (in English) with no labels. Your task is to preprocess the text, develop a sentiment classification model using NLP t…
- Text Preprocessing
- Sentiment Analysis
- Classification
Open coursework 
CodeBeginnerNewBuild a Pricing-Aware Scheduling Agent for Smart Thermostats
Using only the materials provided, build an intelligent agent with four working parts: perception (read the sensor history), learning (cluster each household's comfort intervals…
- Intelligent Agents
- Basic Learning
- Python Programming
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 - CodeIntermediateNew
Add Differential Privacy to a Mental-Health App's Analytics Dashboard
Wrap the analytics module in `analytics_module.py` (provided) with a differential-privacy layer built on OpenDP. Implement epsilon-delta accounting: add Laplace noise to counts …
- Differential Privacy
- Privacy Budget
- Python Programming
Open coursework - CodeBeginnerNew
Predict Subscription Churn for an EdTech Platform
You receive a CSV with about 18,000 student-month rows: features include login frequency, session length, quiz scores, parent app opens, and plan tier. The target is whether the…
- Supervised Learning
- Logistic Regression
- Gradient Boosting
Machine Learning (Undergraduate)
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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