62 in-depth lessons, real Python code, a gamified XP system, and interview prep. Go from zero to AI engineer — at your own pace.
62
Lessons
10
Pages
310+
Quiz Questions
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# Scaled dot-product attention
def attention(Q, K, V):
d_k = Q.shape[-1]
scores = Q @ K.transpose(-2, -1)
scores /= d_k ** 0.5
return softmax(scores) @ V
Everything you need to go from beginner to production ML engineer
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From linear regression to diffusion models — every concept explained with code.
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Earn 100 XP per lesson + bonus XP from quizzes. Level up from Newcomer to Master.
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One ML question + coding challenge + interview question — new every 24 hours.
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Instant feedback, explanations, and bonus XP after every lesson completion.
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Every concept backed by runnable, production-quality Python with one-click copy.
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Activity heatmap, skill radar, quiz stats, bookmarks — see your full journey.
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Ask anything about any lesson — powered by Llama 3.3 70B via Groq API.
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7 foundational AI papers explained in plain English with key ideas and applications.
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25+ ML/DL/NLP/LLM questions across theory, coding, and system design.
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End-to-end projects with architecture, datasets, GitHub, and skills used.
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Track your progress across the entire ML Engineer skill tree node by node.
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Upload any document and ask questions — grounded answers, no hallucination.
62 lessons covering the entire ML ecosystem
Gradient Descent · XGBoost · SVMs · PCA
Backprop · GANs · Diffusion · Autoencoders
Attention · BERT · GPT · LoRA · Fine-tuning
Agents · RLHF · Tool Use · LangChain
Vector DBs · Reranking · Hybrid Search
YOLO · ViT · Segmentation · Transfer
Docker · CI/CD · Drift · Feature Stores
ML System Design · FAANG Q&A
Choose any topic from 8 categories. No prerequisites — start anywhere.
In-depth explanations with runnable Python examples and one-click copy.
Complete lessons to level up from Newcomer to Master, collect 8 badges.
Real-world projects built using the skills from this curriculum
Regression model with feature engineering, EDA, and Ridge/Lasso tuning on the Ames Housing dataset.
Fine-tuned DistilBERT on SST-2 with FastAPI serving — 92% accuracy at <50ms latency.
PDF Q&A using LangChain + FAISS + Groq API. Chunk, embed, retrieve, and generate answers.
Transfer learning on ResNet-50 for 10-class classification. 94% test accuracy with data augmentation.
Telecom churn model with class imbalance handling (SMOTE), SHAP explanations, and Streamlit dashboard.
Custom NER for extracting skills and technologies from job postings using BIO tagging.
10 dedicated pages covering everything from learning to building to interviewing
62 lessons with code, quizzes, AI tutor, notes
Visual learning path from Python to MLOps
ML Engineer tree with per-node progress
9 ML/DL/LLM projects with full architecture
7 foundational AI papers explained simply
Theory, coding & system design questions
New ML + coding + interview Q every day
Upload docs and ask questions — grounded AI
XP, streaks, heatmap, badges, skill radar
Creator profile and portfolio