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Next BatchUpcoming WeekendDeep Learning CourseFrom Foundations to GenAI,Build & Deploy Real AI
Go from Python basics to deploying GenAI apps in production, with live mentorship, real-world projects, and a job-ready portfolio.
Enroll Now - ₹59,999
- 6 Months Duration
12+ Projects Portfolio- 13+ Tools Industry
- 100% Live Sessions
About the ProgramWhat is This Deep Learning Course?
Hands-On GPU Labs
Cloud-based coding labs with pre-configured GPU environments. Train models from your browser, no hardware needed.
1-on-1 Mentorship
Bi-weekly sessions with an industry mentor for career advice, code review, and project guidance.
Career Support
Resume building, LinkedIn optimization, mock interviews, and hiring partner introductions from month 4.
The ProblemWhy most AI courses don't work
The market is flooded with certificates that don't lead to jobs. We built Mindgorithm to fix what's broken.
Build 4-5 Real-World Projects
Not toy datasets.
GenAI + LLMs — The Full Modern Stack
Go beyond CNNs and RNNs.
Deploy to Production — Not Just Notebooks
Learn MLOps, Docker, FastAPI, model serving, and cloud deployment.
1-on-1 Mentorship + Career Support
Bi-weekly mentor sessions, resume reviews, mock interviews, and direct referrals to hiring partners.
The gap isn't knowledge, it's applied skill. Those who can actually build Deep Learning systems will command the biggest career advantage of this decade.
Ready to
future-proof your career?
Join 500+ professionals who've chosen practical AI training.
Who Should JoinIs This Deep Learning Course Right for You?
This program is designed for anyone ready to build real AI skills regardless of their technical background.
Fresh Graduates &
Students
You know Python and want to break into AI.
Working Software
Professionals
You are already coding but want to move into AI/ML.
Career
Switchers
Coming from analytics, data engineering, or non-tech backgrounds?
Developers &
Tech Pros
Add neural networks, LLMs, and computer vision to your engineering skills.
Eligibility: Bachelor's degree with min. 50% • Coding experience NOT required
CurriculumDeep Learning Course Curriculum
9 Modules, 12+ Projects
A practical 6-month deep learning course. Go from Python basics to deploying GenAI apps with 4-5 real-world projects and live mentorship.
Python Foundations + Math Essentials (Preparatory)
Build the foundation — Python and essential math before diving in
- Python for Data Science — NumPy, Pandas, Matplotlib
- Linear Algebra essentials — vectors, matrices, eigenvalues
- Probability, statistics, and distributions for ML
- Calculus refresher — gradients, chain rule, optimization basics
- Jupyter Lab environment setup and best practices
Machine Learning Foundations
Master the algorithms that power AI systems
- Supervised learning — regression, classification, SVMs
- Unsupervised learning — clustering, dimensionality reduction, PCA
- Model evaluation, cross-validation, and hyperparameter tuning
- Feature engineering and data preprocessing pipelines
- Scikit-learn hands-on project: End-to-end ML pipeline
Deep Learning Core — Neural Networks from Scratch
Unlock the full power of neural networks with PyTorch
- Perceptrons, activation functions, forward and back propagation
- CNNs — convolutions, pooling, architectures (ResNet, EfficientNet)
- RNNs, LSTMs, GRUs — sequence modeling fundamentals
- Regularization — dropout, batch normalization, weight decay
- PyTorch deep dive — building and training custom networks
NLP + Large Language Models (LLMs)
From embeddings to fine-tuning modern language models
- Text preprocessing, tokenization, word embeddings (Word2Vec, GloVe)
- Attention mechanism and Transformer architecture — from scratch
- BERT, GPT, T5 — understanding and fine-tuning large language models
- Prompt engineering — zero-shot, few-shot, chain-of-thought
- RAG pipelines — vector databases, LangChain, retrieval-augmented generation
Computer Vision — Detection, Segmentation and Beyond
Teach machines to see, detect, and understand the visual world
- Image classification architectures — VGG, ResNet, Vision Transformers
- Object detection — YOLO, Faster R-CNN
- Image segmentation, transfer learning, and data augmentation
- Video understanding and real-time inference
Reinforcement Learning
Train agents to make decisions and learn from their environment
- Markov Decision Processes, Q-Learning, policy gradients
- Deep Q-Networks (DQN) and actor-critic methods
- RLHF — how ChatGPT-style models are aligned using human feedback
Generative AI — Diffusion Models, GANs and LLM Apps
Build and deploy the AI technologies transforming every industry
- Generative Adversarial Networks (GANs) — architecture, training, applications
- Variational Autoencoders (VAEs) and latent space exploration
- Diffusion models — Stable Diffusion, image generation pipelines
- Building LLM-powered applications — agents, function calling, tool use
- Multi-modal AI — text-to-image, image-to-text, vision-language models
Edge AI + Speech and Audio Processing
Shrink models, run on devices, and process audio and speech
- Model compression — quantization, pruning, knowledge distillation
- Deploying deep learning on edge devices and IoT hardware
- Speech recognition and audio deep learning fundamentals
- On-device inference optimization and TensorRT
MLOps + Production Deployment
Ship your models as real APIs and web apps — capstone included
- Model serving with FastAPI, Flask, and Docker
- CI/CD for ML — experiment tracking with MLflow and Weights and Biases
- Cloud deployment — AWS SageMaker, GCP Vertex AI basics
- Monitoring, versioning, and responsible AI in production
Tools You'll Master
Python
PyTorch
TensorFlow
Hugging Face Transformers
LangChain
OpenAI APIs
Scikit-learn
FastAPI
Docker
MLflow
Weights & Biases
AWS SageMaker
GCP Vertex AIPortfolio ProjectsYou Will Build 12+ Real AI Applications
Not toy examples — applications you can deploy and show employers.
Domain-Specific Chatbot
Build an intelligent chatbot using RAG pipelines, LangChain, and a vector database. Answer questions from your own documents with high accuracy.
- LangChain
- RAG
- Vector DB
- OpenAI
AI Resume Analyzer
Create an NLP-powered screening and scoring engine that parses resumes, matches job descriptions, and ranks candidates automatically.
- NLP
- Transformers
- Hugging Face
- FastAPI
Real-Time Object Detector
Build a YOLO-based real-time object detection system with live video inference. Deploy it as a web app accessible from any browser.
- YOLOv8
- OpenCV
- FastAPI
- WebRTC
AI Image Generator
Fine-tune a Stable Diffusion model and deploy it as a production image generation pipeline with a fully functional API and UI.
- Stable Diffusion
- Diffusers
- FastAPI
- Docker
Recommendation Engine
Design and deploy a deep collaborative filtering recommendation system that personalizes suggestions at scale — similar to Netflix or Spotify.
- PyTorch
- Collaborative Filtering
- FastAPI
- Redis
Medical Image Classifier
Train a CNN-based diagnostic assistance tool on real medical imaging datasets. Apply transfer learning for high-accuracy classification.
- CNN
- ResNet
- Transfer Learning
- PyTorch
Sentiment Analysis Dashboard
Build a real-time NLP pipeline that processes social media feeds, classifies sentiment, and displays live trends on an interactive dashboard.
- BERT
- Transformers
- FastAPI
- WebSockets
RL Game Agent
Train a Deep Q-Network agent with reward-based learning to master a game environment. Observe the agent improve in real time.
- DQN
- PyTorch
- Gymnasium
- RLHF
LLM-Powered Multi-Agent App
Build a multi-agent application using function calling and tool use — agents that browse the web, write code, and coordinate to complete complex tasks.
- LangChain
- Agents
- Tool Use
- OpenAI
Speech-to-Text System
Deploy a Whisper-based transcription pipeline that converts audio and video to accurate, timestamped text — production-ready with a REST API.
- Whisper
- FastAPI
- PyTorch
- Docker
Fraud Detection Model
Build an anomaly detection model on real transaction data. Achieve high precision with ensemble methods and deploy for real-time scoring.
- Anomaly Detection
- XGBoost
- FastAPI
- Pandas
Your Own Capstone
Bring your own problem — we help you scope, build, and deploy it. Your capstone becomes the centrepiece of your portfolio and your story to employers.
- Full Stack
- CI/CD
- Cloud
- MLOps
Build these
projects and more
Graduate with a portfolio that proves your skills — not just a certificate.
Career OutcomesWhere This Deep Learning Course Takes You
Deep Learning skills are in explosive demand. Here are the roles you'll be qualified for.
- ₹12–30 LPA
Deep Learning Engineer
Build and train neural networks at scale
- ₹10–25 LPA
Computer Vision Engineer
Detection, segmentation, and visual AI
- ₹10–26 LPA
NLP Engineer
Language models for search and chat
- ₹14–35 LPA
GenAI / LLM Developer
Specialized skills, premium pay
- ₹12–28 LPA
MLOps Engineer
Ship and scale models in production
Salary ranges are estimates and vary by experience and company.
₹59,999
- Live Saturday & Sunday classes
- Batch starts: Upcoming Weekend
- Duration: 6 months • 100% Live
- Lifetime curriculum updates included
Small Batch Size
Only 50 seats per batch. Personalized instructor support.
Direct Instructor Access
WhatsApp group for quick doubt resolution, answered in hours.
Lifetime Updates
Get all future curriculum updates at no extra cost.
Certificate of Completion
Showcase your skills on LinkedIn and your resume.
Alumni Network Access
Join a growing community of AI practitioners across India.
Frequently Asked QuestionsQuestions? We've got answers.
Deep learning has a reputation for being complex, but it is very learnable with the right structure. This course starts with Python and math foundations before building up to neural networks, so you are never thrown in the deep end. If you can write basic code and are willing to put in consistent effort, you will be building real deep learning models within weeks — not months.
You need basic Python knowledge — variables, loops, functions, and libraries like NumPy. No prior machine learning experience is required. Module 0 covers Python essentials and the math you will need. If you can write a Python script that processes data, you have enough to start.
Graduates are qualified for roles including Deep Learning Engineer, AI/ML Engineer, NLP Engineer, Computer Vision Engineer, GenAI Developer, MLOps Engineer, and Data Scientist. The salary range for these roles in India is ₹8–40 LPA depending on experience and specialization, with GenAI and LLM roles commanding the highest premiums.
The course runs for 6 months with live classes every Saturday and Sunday. You will have access to all recorded sessions and materials for the full 6 months from enrollment.
Premium academic programmes are research-oriented and heavily priced. Our course is designed for practical, job-ready outcomes at a fraction of the cost. We cover modern topics like GenAI, LLMs, RAG pipelines, and MLOps that traditional academic programmes often do not include. You also get a flexible hybrid format and career support from day one — not just a certificate.
You will work extensively with Python, PyTorch, TensorFlow, Hugging Face Transformers, LangChain, OpenAI APIs, Scikit-learn, FastAPI, Docker, MLflow, Weights and Biases, and cloud platforms (AWS/GCP basics). These are the exact tools used in production AI teams today.
Yes. If you are not satisfied within the first 14 days of enrollment, you can request a full refund — no questions asked. We believe in the quality of this programme and want you to experience it risk-free.
Yes. Upon completing all modules and the capstone project, you receive an industry-recognized Advanced Deep Learning Certification. It is a verified digital credential you can share on LinkedIn, and it links directly to your project portfolio — giving employers proof of what you can actually build.
Ready to
Master Deep Learning?
Join the next batch. Learn by building. Walk away with skills that matter.