Computer & Information Sciences
Data Science Challenges
Real data-science projects and challenges on Ewance — clean messy datasets, build and evaluate models, and turn raw data into decisions the way a working data scientist does. Solve them to build a portfolio of verified, recruiter-checkable proof you can do the work — not just describe it.
Recommended challenges
- ResearchIntermediateNew
Red-Team Evaluation of a Refusal Policy
You receive the lab's written refusal policy (version 2.3) and a starter set of 60 red-team prompts (10 per category). Extend the set to 240 prompts (40 per category) using docu…
- Red Teaming
- Refusal Policy
- Alignment Evaluation
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 - DesignSeniorNew
Design a Distributed Training Job for a 13B-Parameter Model
Decide whether to use Fully Sharded Data Parallel (FSDP), Tensor Parallelism, Pipeline Parallelism, or a hybrid; justify against the 13B-param + 32-H100 setup. Calculate memory …
- Distributed Training
- Fsdp
- Pytorch
Open coursework - CodeSeniorNew
Train a GAN for Synthetic Defect Augmentation on a Factory Line
You receive a labeled defect dataset (12 defect types, ranging from 8 to 4,200 examples each), the production classifier, and a starter StyleGAN2-ADA codebase. Train a GAN per r…
- Gans
- Stylegan
- Data Augmentation
Open coursework 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
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 - DesignBeginnerNew
Design a Negotiation Support Tool for Climate-Tech Supplier Contracts
You will design and prototype a negotiation support tool for a single supplier contract with six issues (price per kg, delivery lead time, minimum order quantity, payment terms,…
- Negotiation Modeling
- Decision Support Systems
- Multi Issue Bargaining
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 - DesignBeginnerNew
Build an Attention-Visualization Tool for Translation Quality Audit
You will load a small open-source EN-FR transformer (e.g., Helsinki-NLP Opus-MT-en-fr), build a Streamlit or Gradio demo that lets the user paste English source, see the French …
- Attention Mechanisms
- Neural Mt
- Tool Design
Open coursework - Browse challenges
Explore role
Strategy Analyst
Frame the business question, model the options, build the recommendation. From market sizing to competitive analysis, this role is where strategy consulting meets in-house decision-making.
- CodeIntermediateNew
Variational Autoencoder for Synthetic Tabular Banking Data
You receive a 500K-row anonymized transaction dataset with 25 columns (mixed numerical + categorical). Train a VAE (TabVAE or a small custom model) with appropriate likelihoods …
- Variational Inference
- Deep Generative Models
- Synthetic Data
Open coursework - CodeBeginnerNew
Build a Video-Question-Answering Demo on a Budget
Pick the model (Video-LLaVA, VideoChat2, or LLaVA-Video) and justify on the A10G budget. Build a Streamlit demo: upload video, ask question, get answer with cited frame timestam…
- Video Language Models
- Multimodal Fusion
- Streamlit
Open coursework - CodeIntermediateNew
Wire a Knowledge Graph into a Pharma RAG Assistant
You receive: 100 internal benchmark questions with reference answers; a 50,000-document anonymized RAG index; a curated drug-target-disease KG (~80,000 triples) loaded into a tr…
- Kg Grounded RAG
- Sparql
- Entity Linking
Open coursework - AnalysisIntermediateNew
Run a Pre-Deployment Fairness + Drift Audit on a Hiring Model
You receive a trained classifier (joblib), the training data sample, and a held-out 'next-month' evaluation set. Compute group fairness metrics (false-positive-rate gap, true-po…
- Fairness Metrics
- Drift Detection
- Bias Mitigation
Machine Learning in Practice Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- DesignIntermediateNew
Instrument a Model Monitoring Stack from Scratch
Pick the priority product (recommend the customer-service RAG assistant, around 40k queries/day). Define monitoring signals: input drift (Evidently/NannyML), output quality (LLM…
- Model Monitoring
- Data Drift Detection
- LLM Evaluation
ML Engineering and Production ML - CodeIntermediateNew
Build a Canary Rollout for a Production Recommender
Pick a serving stack (Triton, Seldon Core, KServe, or BentoML). Implement two-model traffic splitting with a configurable percentage (start at 5%). Wire up online metric collect…
- Canary Deployment
- Kubernetes
- Ab Testing
ML Engineering and Production ML - 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 - ResearchSeniorNew
Plan a Parameter-Efficient Fine-Tuning Strategy for a Big-Tech AI Lab
You will produce (1) a 6-page survey of four PEFT methods (LoRA, adapters, prefix tuning, IA3) with their strengths, weaknesses, and parameter footprints, (2) a one-page decisio…
- Parameter Efficient Fine Tuning
- Transfer Learning
- Fine Tuning
Open coursework - DesignBeginnerNew
Design an Automated Essay-Feedback System
You receive 20 anonymized middle-school essays scored by 2 human teachers on a 4-dimension rubric (structure, evidence, voice, mechanics). Design an LLM-based feedback system th…
- Automated Assessment
- Rubric Design
- Prompt Engineering
AI in Education and Learning Analytics - AnalysisBeginnerNew
Map Creator Communities for a Short-Form Video Platform
You receive a 90-day sample of about 4 million creator-creator interactions (duets, mentions, audience overlap) and creator metadata (region, language, content tag). Build a cre…
- Network Analysis
- Community Detection
- Graph Visualization
Open coursework - AnalysisBeginnerNew
Diagnose Churn Drivers for a B2B SaaS Workflow Tool
You receive three CSV exports: 18 months of weekly product-usage events for about 1,800 accounts, the full support-ticket history, and account firmographics (industry, size, pla…
- Exploratory Data Analysis
- Data Wrangling
- Feature Engineering
Applied Data Analysis and Practical Data Science - DesignIntermediateNew
Co-Design a Trust Layer for an Enterprise RAG Assistant
You will plan and run a 5-day remote co-design study with eight pilot users (a mix of plant operators and middle managers). Sessions 1-2: discover where trust breaks down. Sessi…
- Co Design
- User Research
- Trust And Transparency
Human-Computer Interaction for AI Systems - AnalysisIntermediateNew
Compare ML Compiler Stacks on a Vision Backbone
Take a frozen ResNet-50 (or similar) in ONNX. Compile and benchmark it via TensorRT on Jetson + GPU, ONNX Runtime on all three, OpenVINO on x86 CPU, and IREE on ARM if time allo…
- Ml Compilers
- Tensorrt
- Onnx
Open coursework - AnalysisIntermediateNew
Cut Latency and Cost on a High-Volume Summarization Service
You receive 30 days of anonymized request logs (prompt token counts, completion token counts, latencies, models used). Profile the cost and latency distribution, then design and…
- Cost Optimization
- Latency Optimization
- Prompt Compression
Open coursework - CodeBeginnerNew
Reduce Dimensionality on Sensor Streams for a Mid-Cap Robotics OEM
You receive 120 robot-hours of windowed sensor data (5s windows, 240 channels) with labels for normal vs. one of four fault classes. Implement (1) PCA, (2) kernel PCA with an RB…
- Dimensionality Reduction
- Kernel Methods
- Autoencoders
Machine Learning - ResearchIntermediateNew
Run an Adversarial-Robustness Audit on a Face-Liveness Model for a Fintech
You receive a stand-in face-liveness model with the same backbone as the production model plus a labeled evaluation set of 2,000 frames. Apply three standard digital attacks (FG…
- Adversarial Robustness
- Face Liveness
- Pytorch
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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