Generative AI Course
Generative AI certification course
Step into the rapidly evolving world of artificial intelligence with our Generative AI certification course in Vadodara, designed to equip you with the skills to create innovative AI-driven solutions. Generative AI focuses on developing systems that can autonomously generate new content—be it text, images, music, or videos—closely mimicking human creativity. This powerful technology is already transforming industries such as content creation, design, entertainment, and more, with global leaders like OpenAI, Google, and NVIDIA pushing its boundaries.
Our program is widely recognized as the best Generative AI training in Vadodara, thanks to its blend of comprehensive theory and hands-on learning. Throughout the course, you’ll dive into the core principles of cutting-edge generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformer-based architectures.
From the basics to advanced techniques, you’ll learn to build, train, and fine-tune your own generative models using Python and industry-standard tools. Real-world projects and coding assignments will allow you to apply these skills in practical scenarios, ranging from image generation to content synthesis.
What sets this course apart is its emphasis on both technical mastery and ethical awareness. You’ll explore the implications of AI-generated content, including bias, copyright, and responsible use, preparing you to innovate responsibly in this exciting domain.
Ideal for aspiring AI professionals, creatives, and tech enthusiasts, this course also includes personalized guidance and mentorship, making it one of the most effective Generative AI coaching classes in Vadodara.
Upon successful completion, you’ll earn a recognized certification and a digital badge to showcase your expertise—boosting your portfolio and making you more competitive in the job market.
Take the next step in your AI journey with our Generative AI certification course in Vadodara and unlock the future of creative technology.
What will I learn?
- Understand the fundamental concepts and techniques of generative AI.
- Implement and train various generative models using Python and deep learning frameworks.
- Apply generative AI techniques to create new images, text, and other forms of content.
- Evaluate the performance and quality of generative models.
- Explore advanced topics in generative AI, such as style transfer and latent space manipulation.
- Understand the ethical implications and societal impacts of generative AI.
Requirements
- Proficiency in Python programming
- Basic understanding of machine learning and deep learning concepts
- Familiarity with neural networks and deep learning frameworks (TensorFlow, PyTorch)
Generative AI Course Content
- Generative AI
- Why are generative models required?
- Understanding generative models and their significance
- Generative AI v/s Discriminative Models
- Recent advancements and research in generative AI
- Gen AI end-to-end project lifecycle
- Key applications of generative models
- Text Preprocessing and Word Embedding
- Segmentation and Tokenization
- Change Case, Spell Correction
- Stop Words Removal, Punctuations Removal, Remove White Spaces, Stemming and Lemmatization
- Parts of Speech Tagging
- Text Normalization, Rephrase Text
- One hot encoding,
- Index-based encoding
- Bag of words,
- TF-IDF
- Word2Vec,
- FastText
- N-Grams, Elimo
- Bert-based encoding
- Application and use cases of LLMs
- Transfer learning in NLP
- Pre-trained transformer-based models
- How to perform finetuning of pre trained transformer based models
- Mask language modeling
- BERT- Google, GPT- OpenAI
- T5- Google
- Evaluations Matrixs of LLMs models
- GPT-3 and 3.5 Turbo use cases
- Learn how Chatgpt trained
- Introduction to Chatgpt- 4
- Hugging face And its Applications
- Hugging Face Transformers
- Hugging face API key generation
- Hugging Face Transfer learning models based on the state-of-the-art transformer architecture
- Fine-tuning using a pre-train models
- Ready-to-use datasets and evaluation metrics for NLP.
- Data Processing, Tokenizing and Feature Extraction with
- Standardizing the Pipelining
- Training and callbacks
- Language Translation with Hugging Face Transformer
- Generative AI with LLMs and LLM Powered Applications
- Text summarization with hugging face
- Language Translation with Hugging Face
- Transformer
- Text to Image Generation with LLM with hugging face
- Text to speech generation with LLM with hugging face
- Guide to Open AI and its Ready to Use Models with Application
- What is OpenAI API and how to generate OpenAI API key?
- Installation of OpenAI packageExperiment in the OpenAI playground
- How to setup your local development environment
- Different templates for prompting
- OpenAI Models GPT-3.5 Turbo DALL-E 2, Whisper, Clip,
- Davinci and GPT-4 with practical implementation
- OpenAI Embeddings and Moderation with Practical
- Implementation of Chat completion API,
- Functional calling and Completion API
- How to manage the Tokens
- Different Tactics for getting an Optimize result
- Image Generation with OpenAI LLM model
- Speech to text with OpenAIUse of Moderation for content complies with OpenAI
- Understand rate limits, error codes in OpenAPI
- OpenAI plugins connect ChatGPT to third-party applications.
- How to do fine-tuning with custom data
- Project: Finetuning of GPT-3 model for text classification
- Project: Telegram bot using OpenAI API with GPT-3.5 turbo
- Project: Generating YouTube Transcript with Whisper
- Project: Image generation with DALL-EPrompt Engineering Mastering with OpenAI
- Introduction to Prompt Engineering
- Different templates for prompting
- Prompt Engineering: What & Why?
- Prompt Engineering & ChatGPT Custom Instructions
- The Core Elements Of A Good Prompt
- Which Context Should You Add?
- Zero- One- & Few-Shot Prompting
- Using Output Templates
- Providing Cues & Hints To ChatGPT
- Separating Instructions From Content
- Ask-Before-Answer Prompting
- Perspective Prompting
- Contextual Prompting
- Emotional Prompting
- Laddering Prompting
- Using ChatGPT For Prompting
- Find Out Which Information Is Missing
- Self-evaluative Prompting
- ChatGPT-powered Problem Splitting
- Reversing RolesMore Prompts & Finding Prompt Inspirations
- Super Prompts Like CAN & DAN
- Vector database with Python for LLM Use Cases
- Storing and retrieving vector data in SQLite
- Chromadb local vector database part1 setup and data insertion
- Query vector data
- Fetch data by vector id
- Database operation: create, update, retrieve, deletion, insert and update
- Application in semantic search
- Building AI chat agent with langchain and openai
- Weviate Vector Database
- Pinecone Vector Database
- Hands-on with LangChain
- Practical Guide to LlamaIndex with LLMs
- Bonus: Additional Productive Tools to ExploreChainlit ( async Python framework)
- LIDA (Automatic Generation of Visualizations and
- Infographics)
- Slidesgo ( AI Presentation Maker )
- Content Creation (Jasper, Copy.ai, Anyword)
- Grammar checkers and rewording tools (Grammarly, Wordtune, ProWritingAid)
- Video creation (Descript, Wondershare Filmora, Runway)
- Image generation (DALL·E 2, Midjourney)
- Research (Genei, Aomni)
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Why Choose Generative AI Certification Course from Bright Computer Education?
Generative AI courses are designed to deliver an advanced, creative, and hands-on learning experience for individuals interested in the future of artificial intelligence. Whether you’re planning to Learn Generative AI in Vadodara, starting with the basics through Generative AI for beginners in Vadodara, or looking to deepen your expertise with Advanced Generative AI training in Vadodara, these programs are structured to support learners at every level. The curriculum explores deep learning techniques, generative models like GANs and VAEs, text-to-image generation, and real-world AI applications. With project-driven learning, expert mentorship, and access to cutting-edge tools, students gain the skills and confidence to build innovative AI-powered solutions in a rapidly evolving tech landscape.
Designed Curriculum
Our curriculum covers everything from basic to advanced topics. Topics include variables, data types, control structures, functions, OOP, STL, and more.
Hands-on Learning
Dive into practical exercises and coding projects that reinforce learning and help you build real-world applications.
Experienced Instructors
Learn from industry experts with years of experience in C programming and software development.
Flexible Learning
Choose from flexible scheduling options, including self-paced learning or live virtual classes to fit your busy lifestyle.
Career Development
Gain valuable skills sought after by employers in various industries, from software development to embedded systems and beyond.
Interactive Learning
Engage with fellow learners and instructors through live Q&A sessions, discussion forums, and collaborative coding exercises.
Diverse Career Opportunities in Generative AI: Exploring Paths in India's Technology Sector
Generative AI is one of the most transformative fields in artificial intelligence, focused on creating new content—such as text, images, music, and code—using advanced models like GPT, DALL·E, and GANs. A course in Generative AI equips learners with the skills to build cutting-edge applications in content creation, automation, virtual assistants, gaming, and more.
In India, professionals skilled in Generative AI can earn between ₹10–18 lakhs per annum, especially in sectors like tech, media, fintech, and healthcare. Globally, in high-tech hubs like the U.S., UK, Canada, and Singapore, salaries range from $120,000 to $180,000 annually for roles involving AI model development, prompt engineering, and creative automation.
With 2–4 years of experience, learners can grow into roles such as Generative AI Engineer, AI Product Developer, Prompt Engineer, or Research Scientist. Mastery of Python, deep learning frameworks (like PyTorch and TensorFlow), and transformer models is key to succeeding in this space.
In summary, a Generative AI course offers exciting, future-focused career opportunities in India and abroad—perfect for those looking to innovate at the intersection of creativity and advanced technology.
Frequently Asked Questions
The duration of a Generative AI course can vary depending on the program’s structure and intensity. Some comprehensive courses are designed to be completed over several months, providing an in-depth exploration of generative AI concepts and practical applications. Other programs may span several weeks, especially if they include in-depth modules and hands-on projects. The exact timeframe often depends on the learner’s pace and the course’s depth.
No, prior programming experience is not strictly required to enroll in a Generative AI course. Many courses are tailored for beginners, starting with foundational concepts and gradually progressing to more advanced topics. However, having a basic understanding of programming concepts and general computer skills can be beneficial and may enhance the learning experience. Some courses also cover essential programming concepts as part of the curriculum to ensure all learners can follow along.
A comprehensive Generative AI course typically covers a range of topics to equip learners with the necessary skills for developing AI-driven content generation systems. These topics often include deep learning fundamentals, neural network architectures, generative models like GANs and VAEs, natural language processing (NLP), and the application of generative AI in various domains such as text, image, and audio generation. Additionally, courses may delve into tools like TensorFlow and PyTorch. Some programs also incorporate real-world projects to provide practical experience.
Yes, most reputable Generative AI courses offer a certificate upon successful completion. These certificates can validate your generative AI expertise and enhance your professional profile. They can be a valuable addition to your resume or LinkedIn profile, showcasing your skills to potential employers. Some courses also provide assistance with portfolio development to help you demonstrate your competencies effectively.
Support during a Generative AI course varies by provider but often includes access to instructors, discussion forums, and additional learning resources. For instance, some courses offer mentorship, live doubt-clearing sessions, and community support to assist learners in overcoming challenges and to provide a collaborative learning environment. These resources are designed to enhance the learning experience and ensure that students can confidently apply their skills in real-world scenarios.
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