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
- CodeBeginnerNew
End-to-End Lane Following on a Donkeycar Platform
Use the public Donkeycar Tub dataset (or collect about 30 minutes of driving on the simulator). Train a CNN-policy baseline (the Donkeycar default architecture is fine) that pre…
- End To End Learning
- Imitation Learning
- Pytorch Or Tensorflow
AI for Autonomous Vehicles - DesignIntermediateNew
Train a Self-Play Agent for a Card-Game Edtech Demo
Implement a small two-player imperfect-information card game (Kuhn poker or a 3-card simplified Hold'em variant). Implement CFR or CFR+ for the game and run self-play for at lea…
- Counterfactual Regret Minimization
- Self Play
- Game Theory
Artificial Intelligence: Principles and Techniques - DesignFoundationalNew
Build a Tic-Tac-Toe-Style Game Agent for an Edtech Demo
Implement Connect-Four (7-column, 6-row board) in Python plus a minimax agent with alpha-beta pruning, configurable search depth, and a simple heuristic evaluation function for …
- Game Playing Ai
- Minimax
- Alpha Beta Pruning
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
Decision Support Systems and Decision Analysis 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
- CodeSeniorNew
Run a Backpropagation Bug-Hunt on an Open-Source RL Implementation
You receive the offending fork (around 4,000 lines of PyTorch) and three known-failure seeds. Reproduce the NaN failure deterministically, instrument the forward and backward pa…
- Backpropagation
- Pytorch Or Tensorflow
- Debugging
Deep Learning - CodeSeniorNew
Multilingual RAG for a European Customer-Support Knowledge Base
You receive 6,000 documents in 4 languages (mix of FAQs, parts catalogs, repair procedures) plus 120 labeled queries (30 per language) with gold source documents. Build a multil…
- Multilingual RAG
- Cross Lingual Retrieval
- Multilingual Embeddings
Retrieval-Augmented Generation - 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 Or Javascript
- Data Cleaning
- Data Analysis
Programming for Business Applications - ResearchSeniorNew
Self-Supervised Pretraining for a Pathology Foundation Vendor
You receive a public pathology dataset (about 80,000 unlabeled whole-slide-image patches plus a labeled 8,000-patch subtype-classification subset across 4 classes). Pretrain a R…
- Supervised Learning
- Medical Imaging
- Transfer Learning
Machine Learning for Imaging and Medical Image Analysis - 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
Build an Evaluation Harness for an Internal LLM Assistant
You will design and implement an evaluation harness in Python that runs four test suites: (1) helpfulness (LLM-as-judge with rubric), (2) factual grounding (compare cited source…
- LLM Evaluation
- LLM As Judge
- Prompt Injection Testing
Large Language Models - CodeBeginnerNew
Build a Math Intelligent-Tutoring Assistant for High Schoolers
You receive: a curated set of 40 algebra problems with worked solutions, the company's pedagogy rubric ('hint, don't reveal' principle), and a baseline 'just answer' chatbot for…
- Intelligent Tutoring
- Prompt Patterns
- Ai Agents
AI in Education and Learning Analytics - CodeIntermediateNew
Reason over a Climate Policy Knowledge Graph for an EU Think Tank
Design a knowledge graph schema covering regulations, member states, sectors, transposition dates, and source-document citations. Ingest a curated dataset of around 200 nodes th…
- Knowledge Graphs
- Knowledge Representation
- Rule Based Reasoning
Artificial Intelligence: Principles and Techniques - CodeIntermediateNew
Detect Change Points in a Trading Platform's Latency Telemetry
You receive 90 days of per-millisecond latency telemetry across 12 services, plus an incident log of 14 known regressions and 22 known false-alarm-class events. Implement and tu…
- Change Point Detection
- Anomaly Detection
- Time Series Analysis
Time Series Analysis and Forecasting Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- ResearchIntermediateNew
Safety-Test a Customer-Service Agent for Adversarial Prompts
You receive a sandboxed instance of the agent (a tool-using LLM that can read account balances and open support tickets — both mocked). Design a red-team suite of at least 80 pr…
- Ai Agents
- Red Team Operations
- Adversarial Prompts
AI Agents and LLM-Based Agents - CodeIntermediateNew
LoRA Fine-Tune a 7B LLM for Legal-Clause Extraction
You receive a curated extraction dataset (2,000 train, 500 val, 500 test contracts with span-level labels across 12 clause types) and a fine-tunable 7B base model (e.g., Llama-3…
- Fine Tuning
- Fine Tuning
- Parameter Efficient Tuning
Fine-Tuning Large Language Models - ResearchSeniorNew
Structure Learning for a Causal Network in Fintech Risk
You receive the 60-signal dataset and a short interview summary of risk analysts' beliefs about which signals influence which. Use a hill-climbing structure-learning algorithm w…
- Structure Learning
- Bayesian Networks
- Causal Modeling
Probabilistic Graphical Models - CodeIntermediateNew
Prompt-Injection Hardening for a Customer-Support Agent
You receive the current agent prompt, the pen-tester's 60-attack injection test set (direct prompt injection, indirect via doc content, refusal-bypass, and exfiltration), and a …
- Prompt Injection Defense
- System Prompt Design
- Red Team Operations
Prompt Engineering - ResearchBeginnerNew
Evaluate a Generative AI Image Tool with a Within-Subjects Study
You will write a study protocol, recruit 20 participants (a Discord callout is fine), counterbalance the two conditions, and run 45-minute sessions over Zoom. Collect three meas…
- Experimental Design
- User Study
- Within Subjects Design
Human-Computer Interaction for AI Systems - DesignIntermediateNew
Build an OWL Ontology for a Pharma R&D Knowledge Base
You receive a CSV-form starter knowledge base (around 4,000 compounds, 600 targets, 1,200 assays) and a list of 12 competency questions the scientists currently can't answer wit…
- Ontology Design
- Owl
- Knowledge Representation
Fuzzy Logic, Knowledge Representation, and Symbolic Reasoning - AnalysisBeginnerNew
Build a Reproducible Pricing Analysis for a DTC Skincare Brand
You receive 24 months of order-line data (around 480,000 lines), a Shopify-style customer export, and a discount-code log. Build a Python pipeline that produces: SKU-level price…
- Data Wrangling
- Exploratory Data Analysis
- Cohort Analysis
Applied Data Analysis and Practical Data Science - 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
Reinforcement Learning - 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 - ResearchBeginnerNew
Evaluate Open-Source Embedding Models for a Multilingual Help Center
You receive 1,200 labeled (query, relevant-help-article) pairs across 6 languages plus the help-center corpus (~25,000 articles). Index the corpus with each of 4 open-source mul…
- Multilingual Embeddings
- Dense Retrieval
- Ir Evaluation
Information Retrieval and Search - ResearchSeniorNew
Reproduce a Mechanistic Interpretability Result on a Small Transformer
Pick a published mechanistic-interpretability paper that operates on a small (under 1 billion parameter) open-source transformer (e.g., GPT-2 small, Pythia 70M). Set up the envi…
- Mechanistic Interpretability
- Transformer Internals
- Pytorch Or Tensorflow
AI Safety and Alignment - 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
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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