Generative AI & Deep Learning : All Models With Projects

Generative AI & Deep Learning: All Models With Projects by Arunnachal​am Shanmugara​jan is a comprehensive Udemy course that lets you master generative AI and deep‑learning techniques without spending a dime. Updated July 2026, the course targets learners searching for a free generative AI course, deep learning Udemy course, or learn AI online. It blends theory with hands‑on projects, so you finish with practical skills and a Udemy‑issued certificate that validates your new expertise.

What You'll Learn

• Build end‑to‑end generative AI applications that create text, images, or code using Large Language Models.
• Master convolutional neural networks (CNNs) to solve image‑classification and object‑detection problems.
• Learn recurrent neural networks (RNNs) for sequence modeling, speech recognition, and time‑series forecasting.
• Understand the mathematics behind deep‑learning layers, activation functions, and loss optimization.
• Create generative adversarial networks (GANs) that synthesize realistic media from random noise.
• Implement real‑world AI projects step‑by‑step, from data preprocessing to model deployment.
• Apply deep‑learning best practices such as regularization, hyper‑parameter tuning, and model evaluation.
• Analyze ethical considerations and bias mitigation strategies when building generative AI systems.

Course Details

• Instructor: Arunnachal Shanmugara​jan
• Rating: 4.4 stars (based on thousands of reviews)
• Level: Beginner to Intermediate
• Language: English (en‑US)
• Enrolled students: 134,761
• Certificate: Yes, upon completion
• Includes: Lifetime access, mobile‑friendly videos, certificate of completion

What This Course Covers

Generative AI Foundations

• Definition and real‑world use cases of generative AI.
• Overview of diffusion models, transformers, and autoregressive generation.
• Data collection, cleaning, and tokenization for generative tasks.
• Ethical implications, copyright issues, and bias mitigation.

Large Language Models (LLMs)

• Architecture of transformer‑based LLMs such as GPT‑4 and BERT.
• Fine‑tuning techniques for domain‑specific text generation.
• Prompt engineering strategies that improve output quality.
• Evaluation metrics like perplexity, BLEU, and ROUGE.

Convolutional Neural Networks (CNNs)

• Core concepts: convolution, pooling, and stride.
• Building image classifiers with popular architectures (LeNet, ResNet, EfficientNet).
• Transfer learning using pre‑trained models on custom datasets.
• Visualization of feature maps and activation heatmaps.

Recurrent Neural Networks (RNNs) & Sequence Models

• Understanding vanishing gradients and gated units (LSTM, GRU).
• Implementing language modeling, sentiment analysis, and speech‑to‑text pipelines.
• Sequence‑to‑sequence learning with attention mechanisms.
• Performance benchmarking on benchmark datasets (IMDB, TIMIT).

Generative Adversarial Networks (GANs)

• Theory behind the generator–discriminator game.
• Training stability tricks: Wasserstein loss, spectral normalization, and progressive growing.
• Applications: image synthesis, style transfer, and data augmentation.
• Hands‑on project creating a GAN that generates realistic handwritten digits.

Hands‑On Projects & Deployment

• End‑to‑end project workflow from hypothesis to production.
• Using PyTorch and TensorFlow for model implementation.
• Containerizing models with Docker for scalable deployment.
• Monitoring and updating models in a live environment.

Who Should Take This Course

• Beginners who want a solid grounding in AI and deep learning fundamentals.
• Computer‑science students preparing for AI‑focused capstone projects.
• Software developers transitioning to machine‑learning engineering roles.
• Data analysts aiming to add generative AI capabilities to their toolkit.
• Researchers who need practical implementation experience with LLMs, CNNs, RNNs, and GANs.

Prerequisites

• No prior experience needed — this course is beginner‑friendly.
• Basic programming knowledge in Python is recommended for smoother code execution.
• Familiarity with linear algebra and probability concepts helps but is not mandatory.

Why Enroll in This Course

The course delivers a complete AI curriculum at 100 % off for a limited time, making it one of the rare free coupon opportunities on Udemy in 2026. Because the material is constantly updated, you gain current knowledge that aligns with industry standards. Compared with other paid alternatives, this course offers a balanced mix of theory, code labs, and real‑world projects without hidden fees.

Course Highlights

• Lifetime access to all video lessons and downloadable resources.
• Self‑paced learning allows you to progress according to your schedule.
• Certificate of completion that can be added to LinkedIn or a résumé.
• Mobile‑friendly platform lets you study on smartphones or tablets.
• Hands‑on projects provide a portfolio‑ready showcase for employers.
• 30‑day money‑back guarantee (if you later decide the free enrollment isn’t right for you).

Frequently Asked Questions

Q: Is this course really free?
A: Yes, the course can be accessed at no cost while the free‑coupon promotion remains active. Udemy does not charge any hidden fees, and you retain full access to all materials after enrollment.

Q: What will I learn in this generative AI course?
A: You will master major deep‑learning models—including LLMs, CNNs, RNNs, and GANs—while completing practical projects that generate text, images, and predictions. The curriculum covers both theoretical foundations and step‑by‑step implementation.

Q: Do I get a certificate after completing this course?
A: A Udemy‑issued certificate of completion is awarded automatically once you finish all required lectures and assignments. The certificate can be shared publicly to validate your new skills.

Q: Is this course suitable for beginners?
A: Absolutely. The instructor starts with fundamental concepts before progressing to advanced topics, making it ideal for learners with little or no prior AI experience.

Q: How long do I have to enroll for free?
A: The free‑coupon is available for a limited period, typically a few weeks, and may expire without notice. Enroll as soon as possible to guarantee 100 % off the regular price.

Final Thoughts

If you want to dive deep into Generative AI & Deep Learning: All Models With Projects, this Udemy offering equips you with the knowledge, tools, and portfolio pieces