AI & Data
Deep Learning Challenges
Deep Learning challenges put you inside the work of building models that learn from raw data. You'll develop skills in Neural Networks and Feedforward Networks, apply Data Augmentation, and train models in PyTorch or TensorFlow alongside Reinforcement Learning fundamentals.
From there you'll handle the harder edges — Transformer architecture, Attention mechanisms, Custom architecture design, and Distributed training — working with PyTorch Lightning / Hugging Face Trainer, JAX research patterns, and Ablation study design the way research teams actually do. Each challenge you solve earns a verified credential you can share with recruiters.
Recommended Challenges
· Distributed training Clear- 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 Or Tensorflow
Machine Learning Systems - CodeSeniorNew
Auto-Tune a Distributed Training Cluster's Throughput
Pick a representative fine-tune job (an open 7B model on a public instruction dataset is fine). Define the search space: NCCL_ALGO, NCCL_PROTO, num_workers, prefetch_factor, gra…
- Distributed Training
- Hyperparameter Tuning
- Nccl
Machine Learning Systems - ResearchSeniorNew
Design a Distributed-Training Strategy for a Mid-Sized LLM
You will write a 5-page design memo that picks a parallelism strategy for fine-tuning a 13B model on 32 H100 GPUs, with a tokens-per-second estimate, a memory-per-GPU calculatio…
- Distributed Training
- Parallelism Strategies
- LLM Training
Machine Learning at Scale
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.
Industry teams behind a decade of practitioner briefs
Hiring from this pool?
Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.



















































































