Generative AI Training in Hyderabad
with
100% Placement Assistance
Table of Contents
ToggleGenerative AI Training in Hyderabad
Batch Details
Trainers Name: | Dr. Srinivas Rao, Madhuri |
Trainers Experience: | 13+ Years, 22+ Years |
Next Batch Date: | 2nd Sept(offline),5th Sept(online) |
Training Modes: | Online and offline Training (Instructor-Led) |
Course Duration: | 3 months(offline & online) |
Call us at: | +91 81868 44555 |
Email Us at: | brollyacademy@gmail.com |
Demo Class Details: | ENROLL FOR FREE DEMO CLASS |
Generative AI Course Content
- Introduction to Generative AI.
- AI vs ML vs DL vs NLP vs Generative AI.
- Generative AI principles.
- What is the role of ML in Gen-AI.
- Different ML techniques (Supervised, Unsupervised, Semi-supervised & Reinforcement Learning).
- Applications in various domains.
- Ethical considerations.
- NLP essentials.
- Basic NLP tasks.
- Different text classification approaches.
- Frequency-based – Bag of words, TF-IDF, N-gram.
- Distribution Models – CBOW, Skipgram(Traditional approaches)and
word2vec, Glove. - Ensemble Methods (Random Forest, Gradient Boosting, AdaBoost) &
Traditional Machine Learning Models – Naïve Bayes, Support Vector
Machine (SVM), Decision Trees, Logistic Regression. - Deep learning techniques – CNNs, RNNs, LSTMs, GRU and
Transformers.
- Autoencoders.
- VAE’s and applications.
- GANs and it’s applications.
- Different types of GANs and applications.
- Different types of Language models
- Applications of Language models
- Transformers and its architecture
- BERT, RoBERTa, GPT variations
- Applications of transformer models
- What is Prompt Engineering
- What are the different principles of Prompt Engineering
- Types of Different Prompt Engineering Techniques
- How to Craft effective prompts to the LLMs
- Priming Prompt
- Prompt Decomposition
- Generative AI lifecycle
- What is RLHF
- LLM pre-training and scaling
- Different Fine-Tuning techniques
- What are word embeddings
- What is the use of word embeddings, where we can use it?
- Word Embeddings – Word2Vec, GloVe and FastText
- Contextual Embeddings – ELMo , BERT and GPT
- Sentence Embeddings – Doc2Vec, Infersent, Universal Sentence
Encoder - Subword Embeddings – BPE(Byte Pair Encoding), Sentence Piece
- Usecase of Embeddings.
- What is Chunking
- What is the use of chunking the document
- What are the traditional effective chunking techniques
- What are the problems and limitations with traditional chunking
techniques? - How to overcome the limitations of Traditional chunking
- Advanced Chunking Techniques:
1. Character Splitting
2. Recursive Character Splitting
3. Document based Chunking
4. Semantic Chunking
5. Agentic Chunking
- What is RAG
- What are the main components of RAG
- High level architecture of RAG
- How to Build RAG using external data sources
- Advanced RAG
- What is Langchain
- What are the core concepts of Langchain
- Components of Langchain
- How to use Langchain agents
● LlamaIndex
● What are Vector Databases
● Why do we prefer Vector Databases over Traditional Databases
● Different Types of Vector Databases: OpenSource and Close Source
● OpenSource: Chroma DB, Weaviate,Faiss,Qdrant
● Close-Source Vector Databases:Pinecone,ArangoDB,Cloud-Based
Solutions
- Supervised Finetuning
- Repurposing-Feature Extraction
- Advanced techniques in Supervised Finetuning -PEFT -LoRA, QLoRA
- Text based LLMs:
Automatic Evaluation: BULE Score, ROUGE Score, METEOR, BERT
Score.
Human Evaluation: Coherence, Factuality, Originality, Engagement - Image based LLMs:
Automatic Evaluation: Pixel-level metrics, FID (Frechet Inception
Distance), IS (Inception Score), Perceptual Quality Metrics,
Diversity Metrics.
Human Evaluation: Photorealism, Style, Creativity, Cohesiveness - Audio generation LLMs:
Automatic Evaluation: FAD (Frechet Audio Distance), IS (Inception
Score), Perceptual Quality Metrics – PAQM, PAQM – SNR (Signal-to-Noise Ratio), PAQM – PESQ (Perceptual Evaluation of Speech
Quality)
Human Evaluation:Perceptual Quality – PQ, PQ- Naturalness, PQFidelity, PQ- Musicality, Task Specific Evaluation. - Video Generation LLMs:
Automatic Evaluation: FVD (Frechet Video Distance), Inception
Score(IS), Perceptual Quality Metrics, Motion Based Metrics –
Optical Flow Error, Content-Specific Metrics.
Human Evaluation: Visual Quality, Temporal Coherence, Content
Fidelit.
- Model Deployment and Management
- Scalability and Performance Optimization
- Security and Privacy
- Monitoring and Logging
- Cost Optimization
- Model Interpretability and Explainability.
- Amazon Bedrock, Azure OpenAI
- ChatGPT, Gemini, Copilot
Generative AI Training In Hyderabad
Key Points
01
In-depth coverage of essential artificial intelligence concepts, algorithms, and applications.
02
We have Trained and experienced faculty for over 12 years with a deep understanding of AI methodologies.
03
Opportunities to work on real-world AI problems to reinforce theoretical knowledge.
04
Well-equipped classrooms and laboratories with the latest technology infrastructure.
05
Dedicated placement support to connect participants with potential employers.
06
We offer Flexible Learning Options for both offline and online courses.
07
Coding sessions and practical exercises to strengthen technical abilities.
08
Recognized certification upon successful completion of the Generative AI training program.
09
We offer the course at an affordable price without compromising the quality of the training.
10
Get to utilize our free 3-day demo sessions before joining the main course.
11
Join a community of like-minded learners and professionals, providing networking opportunities and collaboration.
12
Our course content is regularly updated to include the latest advancements and trends in AI.
13
Engage in interactive learning sessions that make complex AI concepts easier to understand and remember.
14
Enjoy lifetime access to course materials and resources, allowing you to revisit and reinforce your learning anytime.
Overview of Generative AI Training in Hyderabad
The Generative AI course provides participants with a complete understanding of the principles, techniques, and applications of Generative AI, a transformative field within artificial intelligence. Designed to serve to a broad audience, from beginners to seasoned professionals, the course offers a structured curriculum that encompasses both theoretical foundations and practical implementation aspects.
Participants will embark on a journey through the core concepts of Generative AI, delving into the workings of state-of-the-art models like Generative Pre-trained Transformers (GPT).
The curriculum covers essential topics such as natural language processing, image synthesis using Generative Adversarial Networks (GANs), and the integration of Generative AI into real-world applications. Emphasis is placed on hands-on experience, enabling participants to develop proficiency in programming languages like Python and gain practical skills in utilizing popular frameworks such as TensorFlow and PyTorch.
What is Generative AI?
Generative AI is a cutting-edge technology that falls under the broader category of artificial intelligence (AI). It refers to systems and models designed to generate content, often in the form of text, images, or other media, using advanced machine-learning techniques.
The primary goal of Generative AI is to create human-like outputs by learning patterns and structures from vast datasets. This technology has gained prominence in various fields, including natural language processing, computer vision, and creative arts.
One of the key aspects of Generative AI is its ability to understand and replicate human-like language. Natural language processing models, such as GPT (Generative Pre-trained Transformer), are examples of Generative AI systems that excel in understanding context, generating coherent text, and even engaging in meaningful conversations.
These models are pre-trained on extensive datasets, allowing them to learn grammar, semantics, and contextual cues to produce contextually relevant and fluent content.
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Why is Generative AI Used?
Content Creation and Automation:
Generative AI, like GPT models, is great for creating content. It can automatically write articles, blog posts, marketing material, and social media updates. This helps save time and effort for individuals and businesses by making content creation faster and easier.
Natural Language Processing (NLP):
In NLP, Generative AI is used to understand and generate human-like text. This makes it perfect for chatbots, virtual assistants, and automated customer service. It can understand context and give relevant responses, improving how people interact with technology.
Image Synthesis and Manipulation:
Generative AI, especially through Generative Adversarial Networks (GANs), is employed for image synthesis and manipulation. This is valuable in creative fields, allowing for the generation of realistic images, style transfer, and even the creation of entirely new visual content. It finds applications in art, design, gaming, and virtual reality.
Data Augmentation:
In fields where large datasets are essential for training machine learning models, Generative AI is used for data augmentation. It can generate additional training samples, helping improve the robustness and generalization of models. This is particularly beneficial in computer vision tasks and other domains where large labeled datasets are challenging to obtain.
Innovations in Research and Development:
Generative AI facilitates innovation in research and development by providing tools for exploring and experimenting with new ideas. Researchers use these models to generate hypotheses, simulate scenarios, and test various concepts in a more efficient and scalable manner.
Personalization and Recommendations:
In sectors like e-commerce and content streaming, Generative AI is employed to personalize user experiences. By analyzing user behavior and preferences, AI models can generate personalized recommendations, leading to improved user engagement and satisfaction.
Voice and Speech Generation:
Generative AI can be used to create natural-sounding voices for virtual assistants, audiobooks, and automated announcements. It can also help in dubbing and translating content into different languages.
Game Development:
In game development, Generative AI can create new levels, characters, and stories, making games more engaging and diverse without needing as much manual work from developers.
Education and Training:
AI-generated simulations and interactive content help in education by providing personalized learning experiences and training simulations, making learning more engaging and effective.
Music and Art Creation:
Generative AI can compose music and create artwork, opening up new possibilities in the creative industries. It can also assist artists and musicians in exploring new styles and techniques.
Financial Forecasting and Analysis:
In finance, Generative AI can analyze market trends and generate forecasts, helping businesses and investors make more informed decisions.
Course outline
- Overview of generative AI concepts and applications.
- Basic programming skills using Python.
- Essential mathematical concepts for AI, including linear algebra and probability.
- Introduction to machine learning, covering supervised and unsupervised learning.
- Understanding key generative models like GPT and GANs.
- Applications of generative AI in NLP, including text generation and sentiment analysis.
- Practical application of learned concepts through coding projects.
- Addressing ethical implications and responsible AI deployment.
- Exploring how generative AI is used in industries like healthcare, finance, and arts.
- Presenting and discussing individual or group AI projects.
Learning Modes Generative AI Training in Hyderabad
Online Training
- Basic to advance level
- Daily recorded videos
- Capstone Project
- Internship Provided
- 100% Placement assistance
- Whatsapp Group Access
Offline Training
- Lifetime Video Access
- Basic to advance level
- Internship till you get placed
- One-One Mentorship
- Real time Industry Projects
- Interview Guidance
Corporate Training
- Basic to advance level
- Flexible Batch Timings
- Live project included
- Daily recorded videos
- Doubt Clearing Sessions
- Whatsapp Group Access
Generative AI Course Job support program
Career Counseling
Individualized sessions with experienced career counselors to identify personalized career goals and strategies. Guidance on building a strong professional network within the AI industry.
Industry Connections
Access to networking events, webinars, and exclusive job fairs featuring prominent AI companies. Opportunities to connect with alumni who have successfully transitioned into AI roles.
Job Search Assistance
Guidance on navigating job boards, AI-specific job portals, and other relevant platforms. Support in identifying suitable job opportunities aligned with individual career goals.
Continuous Learning Resources
Access to updated AI resources, workshops, and webinars to stay current with industry trends. Discounts on advanced AI courses for ongoing skill development.
Mentorship Program
Matching participants with experienced mentors in the AI field for ongoing support and advice. Regular mentorship sessions to discuss career progression and overcome challenges.
Industry-Specific Workshops
Regular workshops on emerging trends, tools, and methodologies within the AI industry. Hands-on sessions with industry experts to deepen practical understanding of AI applications.
Market Trend in Generative AI
01.
The Generative AI market is anticipated to reach a substantial market size of US$66.62 billion by the year 2024.
02.
The market is expected to exhibit a robust annual growth rate, with a Compound Annual Growth Rate (CAGR) of 20.80% from 2024 to 2030.
03.
The continuous growth trend suggests that the market volume is projected to expand significantly, reaching an estimated US$207.00 billion by the year 2030.
04.
Generative AI is becoming an integral part of various sectors such as healthcare, finance, manufacturing, and more.
05.
contributing to the sustained growth rate as businesses recognize the transformative potential of generative models.
06.
As Generative AI becomes more pervasive, its integration into everyday applications, from virtual assistants to creative design tools.
Student Testimonials Generative AI Training
Saikumar
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@saikumar
Minakshi Thakur
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@minakshithakur
I had a great experience with the Generative AI training at Brolly Academy in Hyderabad. The real-world examples and hands-on projects were very useful and helped me understand how to apply what I learned in practical situations. The instructors were very supportive, always available to help with questions, and made the learning process smooth and enjoyable.
Alka
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@alka
Sudhir Narayan
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Mithali
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@mithali
Pranav
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@pranav
Generative AI Course Certification
- Generative AI Specialist Certification
- Certified GPT Developer
- Generative Adversarial Networks (GANs) Practitioner Certification
- Advanced Natural Language Processing (NLP) for Generative AI
- TensorFlow for Generative Models Certification
- PyTorch for Image Synthesis Certification
- AI Ethics and Responsible AI Deployment Certification
- Certified Generative Model Developer (CGMD)
![](https://brollyacademy.com/wp-content/uploads/2024/08/Certification-1024x723.jpeg)
![](https://brollyacademy.com/wp-content/uploads/2024/08/Certification-1024x723.jpeg)
Skills develop after Gen AI course
- Mastering Python and using tools like TensorFlow and PyTorch for AI implementation.
- Understanding how models like GPT and GANs work in generative AI.
- Proficiency in working with language data for tasks like sentiment analysis and text summarization.
- Creating and manipulating realistic images using algorithms like GANs.
- Effectively managing and preprocessing large datasets for model training.
- Grasping essential machine learning concepts for generative AI applications.
- Understanding basic math and statistics for developing AI algorithms.
Tools covered in Generative AI Training in Hyderabad
- TensorFlow
- PyTorch
- Jupyter Notebooks
- Hugging Face Transformers
- Keras
- NLTK (Natural Language Toolkit)
- OpenCV
- GANLib
Job opportunities after Generative AI course
Natural Language Processing (NLP) Specialist
AI Product Manager
AI Consultant
Placement program of Generative AI Training
Networking Opportunities
Internship Opportunities
Career Guidance and Counseling
Job Matching Algorithm
Resume Enhancement Workshops
Mock Interviews and Skill Assessments
Pre-requisites
Generative AI course In Hyderabad
A solid grasp of basic programming concepts is a fundamental prerequisite. Participants should be comfortable with at least one programming language, such as Python.
Participants should have the ability to write and understand code.
The Generative AI program offers an immersive learning experience in artificial intelligence.
The course has prerequisites to ensure participants have a foundational understanding to derive maximum benefit.
While the program covers machine learning concepts in-depth, a basic understanding of machine learning principles, including supervised and unsupervised learning and common machine learning algorithms, is beneficial.
Participants should have experience working with data, including data preprocessing, cleaning, and basic analysis. Understanding how to manipulate data using libraries like pandas or NumPy will be advantageous for the course.
Frequently Asked Questions - Generative AI Course
Generative AI refers to a subset of artificial intelligence focused on creating or generating new content, such as images, text, or other data. It often involves the use of advanced algorithms and models, such as Generative Adversarial Networks (GANs) and language models like GPT (Generative Pre-trained Transformer). Generate AI has applications in various domains, from creative arts to data synthesis.
While traditional AI focuses on tasks like classification and prediction, Generative AI specializes in content creation. It involves training models to generate new data rather than making predictions based on existing data. This makes Generative AI well-suited for creative applications and tasks that involve generating novel content.
Generative AI finds applications in diverse fields. Some key areas include:
- Image Synthesis and Manipulation
- Natural Language Generation
- Creative Arts and Design
- Data Augmentation
- Content Creation for Virtual Assistants and Chatbots
To delve into Generative AI, having a solid understanding of programming, especially in languages like Python, is beneficial. Additionally, a grasp of machine learning fundamentals, including concepts like neural networks, is advantageous. Familiarity with frameworks like TensorFlow or PyTorch is also helpful.
Yes, Generative AI often involves the use of tools such as TensorFlow, PyTorch, and specific libraries like Hugging Face Transformers for natural language processing tasks. Additionally, depending on the application, tools like GANLib for Generative Adversarial Networks may be utilized.
Ethical considerations in Generative AI include addressing bias in generated content, ensuring responsible deployment to avoid misinformation or malicious use, and maintaining transparency in the development process. Ethical AI practices are crucial to mitigate potential societal risks.
Certainly! Generative AI is actively used in:
- Creating realistic deep fake videos
- Generating human-like text in natural language processing tasks
- Synthesizing high-quality images for creative purposes
- Enhancing data sets through data augmentation
While a computer science background is advantageous, it’s not mandatory. Many online courses and resources cater to beginners, providing a gradual introduction to programming and machine learning concepts. A strong interest and commitment to learning are essential.
Upon completing a Generative AI course, individuals can pursue careers as:
- AI Researchers/Scientists
- Data Scientists
- Machine Learning Engineers
- Natural Language Processing Specialists
- Computer Vision Engineers
- AI Product Managers
- Creative Technologists/Artists
- AI Consultants
Generative AI training in Hyderabad fee will be provided by the concern team.