Generative AI Training In Hyderabad
with
100% Placement Assistance
- Capstone Projects
- Industry Ready Curriculum
- Start From Foundation Level Training
Generative AI Training In Hyderabad
Batch Details
Trainer Name | Madhumathi, Dr. Prasad |
Trainer Experience | 10+ Years, 20+ Years |
Next Batch Date | 15th Oct 2024 (1:00 PM IST Offline) (8:00 PM Online) |
Training Modes | Classroom Training (Hyderabad), Online Training |
Course Duration | 3 Months |
Call us at | +91 9885044555 |
Email Us at | genaimasters@gmail.com |
Demo Class Details | Click Here to Chat on Whatsapp |
Generative AI Training In Hyderabad
Course Curriculum
- Intro – Programing Cycle of Python, Python IDE, Variables, Data type.
- Operator, Decision making & Control flow statements.
- Mathematical functions, Random function, Trigonometric function.
- Strings, Number type conversion.
- List, Tuples, Sets, Dictionary – Functions & Methods.
- Date & time, Calendar module and Time module.
- Functions, Modules, Packages.
- Files in Python, Directories and Exception Handling
- OOPS concepts, Class, Objects, Inheritance, Overriding methods like _init_, Overloading operators, Data hiding.
- Regular Expressions – match function, search function, matching vs searching
Regular exp modifiers and patterns. - Introduction to Flask framework, overview, environment, Apps life cycle, creating views Application.
- Python Libraries – NumPy, Pandas, Matplotlib.
Introduction to Machine Learning / Deep Learning / Artificial Intelligence (AI)
- Understanding Machine Learning Fundamentals, Limitations of ML,
- Deep Learning, AI vs ML vs Generative AI.
- Python revision, Introduction to TensorFlow and Keras.
- Optimization, Derivatives, Function, Probability,
- Scalar-Vector-Matrix, Vector Operation, Vector spaces.
- Principles of Regression and Classification Model,
- Assumptions, Model Evaluation Matrices.
Machine Learning:(Segmentation)
- K-Means & Hierarchical Clustering
Machine Learning:(Bagging)
- Understanding Bagging Concepts, Decision Tree, Random Forest
- Understanding Boosting Concepts, XGBM.
- Understanding Human Brain’s functionality,
- Gradient Descent Optimization.
- Neural Network Overview
- Neural Network Processing, Backward Propagation
- Train, Test & Validation Set, Vanishing & Exploding Gradient,
- Dropout, Regularization, Bias correction, learning rate, Tuning, SoftMax etc.
- Adam, Ada, AdaBoost, RMS Prop etc.
- What is Computer Vision?, Read in Images in Python,
- Introduction to OpenCV, Basic Image Conversions, Image Resizing,
- Image Transformations, Contrast Stretching.
- Introduction to CNN architecture, Convolution, Feature detector, Padding, Stride,
- Activation function, Pooling, Training CNN, Loss function.
- Object detection concepts, Bounding box, object detection models,
- Pre-trained models, Transfer learning, Segmentation concepts.
- Advanced CNN models applications, Face detection,
- RCNN, Fast RCNN, Faster RCNN, Mask RCNN, YOLO.
- Text pre-processing, Binary weight, BoW, TF-IDF,
- Spam detection / Sentiments Analysis, Named Entity Recognition.
- Working with word vectors, Word Embedding, Word2Vec, CBOW/Skip-gram.
- Idea behind RNN architecture,
- Vanishing/Exploding gradient problem.
- LSTM, GRU, RNN vs LSTM vs GRU, Training of RNN model.
- Sequential data analysis, seq2seq model, Encoder-Decoder Architecture,
- Application of seq2seq models.
- Idea behind Transformer, Architecture and Analysis, Pre-trainer models,
- Attention (Elmo, BERT, T5), Self-Attention, Transformer Block, Multi-Head Attention.
- Generative AI using LLM,
- Introduction to GPT, VAE, GANs.
- DCGAN – Intuition, MNIST dataset, Building the generator, Building the discriminator,
- Loss (error) calculation, WGAN – Intuition.
- Pretrained Models (GPT, BERT, BART, T5), Models with applications,
- Intro to Different types of Transformer encoder models- Basic BERT, RoBERTa, DistilBERT etc.
- Basics of Autoencoders, Different types of autoencoders,
- applications with examples of autoencoders, variational autoencoders.
- ChatGPT, Bing, Bard
- Introduction, Automated Speech Recognition,
- text to speech conversion, voice assistant devices.
- Intro to RL, Q-Learning concept examples, Q-learning applications, Exploration & Exploitation.
- Policy gradient concepts, Actor-Critic methods, Proximal policy Optimization (PPO),
- Work with deep RL libraries.
LLM
- Real-world applications and case studies of LLMs,
- Chatbot Creation.
Finetuning LLM using Transformers for different tasks
- Fine-tuning a model process,
- LSTM vs GRU,
- Fine tuning Transformers model.
Evolution of GenAI
- History Of Generative AI,
- Generative AI (GenAI): The evolution of creativity through technology.
GenAI Models and Basic: GPT Models with Prompt Engineering
- ChatGPT- GPT-2, GPT-3, GPT-3.5,
- LLAMA-2,
- Open Chat Model,
- Prompt Engineering Hallucination in LLM.
Finetuning LLM LLAMA-2
- Simple finetuning of LLM: LLAMA-2.
Trainer Details - Generative AI Training in Hyderabad
Ms. Madhumathi
Principal Data Scientist & Generative AI Strategist
10+ Years of Experience
About the Tutor
As an industry expert in Generative AI and an accomplished lead trainer, she is dedicated to advancing students’ careers by integrating real-time applications into Data Science and Generative AI education.
Mr. Prasad
Generative AI Authority & Principal Data Scientist
20+ years of Experience
About the Tutor
Our trainer is an Expert in AI specialist and Lead Data Scientist with deep expertise in Machine Learning, Deep Learning, NLP, Python/R, along with Statistical, Biological, and Panel Analysis.
The trainer has extensive experience in the healthcare and medical fields, having managed projects across the US, UK, Australia, and Canada. He possesses strong expertise in image processing for various diseases, utilizing Generative AI techniques.
Why Choose us for Generative AI Training
Expert Faculty
Generative AI Masters has a team of experienced instructors who are industry experts in Generative AI. Their deep knowledge and practical experience ensure high-quality training.
Comprehensive Curriculum
The training program covers a broad range of topics, including foundational concepts, advanced techniques, and real-time applications of Generative AI, providing a thorough understanding of the field.
Hands-On Learning
The course includes practical sessions and projects that allow students to apply theoretical knowledge to real-time problems, enhancing their learning experience and skill development.
Industry-Relevant Projects
Students get the opportunity to work on industry-relevant projects that reflect current trends and challenges in Generative AI, preparing them for real-time scenarios.
State-of-the-Art Facilities
The institute is equipped with advanced technology and software necessary for Generative AI training, ensuring that students have access to the latest tools and resources.
Personalized Support
We at Generative AI Masters provides individualized attention and mentorship to help students with their unique learning needs and career goals, with a supportive learning environment.
Career Assistance
The institute offers career guidance, including resume building, interview preparation, and job placement assistance, to help students transition smoothly into the industry.
Networking Opportunities
Students have access to a network of professionals, industry leaders, and alumni, providing valuable connections and opportunities for collaboration and growth.
Flexible Learning Options
We Generative AI Masters offers various learning formats, including online, in-person, and hybrid options, helping to different learning preferences and schedules.
Strong Reputation
The institute has a proven track record of success, with positive reviews from past students and praise from industry professionals, reflecting its credibility and effectiveness in Generative AI training. in Hyderabad.
Modes - Generative AI Course in Hyderabad
Classroom Training
- Interactive Face-to-Face Teaching
- Industry Expert Trainers
- Instant Feedback
- Collaborative Tasks
- Hands-on Industry Projects
- Group Discussions
- Covers Advanced Topics
Online Training
- Virtual Learning Sessions
- Daily Session Recordings
- Instructor Support
- Interactive Webinars
- Digital Learning Modules
- Online Practical Labs
- Flexible Learning Schedules
Corporate Training
- Customized Training Programs
- Daily Recordings
- Interactive Team Development
- Expert Instruction
- Industry-Relevant Content
- Performance Monitoring
- On-Site Workshops
What is Generative AI
- Generative AI is a type of artificial intelligence that creates new content, such as text, images, or music.
- It uses advanced algorithms and neural networks to generate outputs that are not just copies of existing data.
- Generative AI models learn patterns and structures in data to produce unique and realistic results.
- Popular types of generative AI include Generative Adversarial Networks (GANs) and Transformers.
- It can be used in various fields, from content creation and art to scientific research and simulations.
- Generative AI is capable of generating creative outputs that mimic human-like creativity.
- It is widely used in industries like entertainment, design, and technology for tasks such as image synthesis and text generation.
- As it grows, Generative AI is raising important discussions about ethics, originality, and the implications of AI-generated content.
- If you are looking to learn Generative AI from industry expert trainers then Generative AI Masters is the Best option
Tools Covered as part of Generative AI Training
In Generative AI training, participants usually learn to use different tools and software that are important for building and handling generative AI models.
These tools include:
TensorFlow
An open-source machine learning framework widely used for building and training neural networks.
PyTorch
A popular deep learning library that provides flexibility and ease of use for creating generative models.
Keras
A high-level API for building and training deep learning models, often used with TensorFlow.
Hugging Face Transformers
A library that provides pre-trained models and tools for natural language processing and other generative tasks.
OpenAI GPT
A powerful language model used for generating human-like text based on input data.
Jupyter Notebooks
An interactive environment for writing and running code, analyzing data, and visualizing results.
NVIDIA CUDA
A parallel computing platform and API model that accelerates computations for deep learning models.
Google Colab
A cloud-based environment that allows for easy development and sharing of Jupyter notebooks for AI projects.
Docker
A tool for packaging applications, useful for deploying and managing AI models in various environments.
Skills Develop After Generative AI Training
- Proficiency in designing and implementing generative AI models for various applications.
- Ability to create realistic content such as text, images, and audio using advanced AI techniques.
- Understanding of key concepts in machine learning and deep learning essential for generative AI.
- Knowledge of different generative models like GANs and Transformers and their practical uses.
- Experience in applying generative AI solutions to real-world projects and case studies.
- Skills in evaluating and fine-tuning AI models to improve performance and accuracy.
- Familiarity with ethical considerations and best practices in deploying generative AI technologies.
- Competence in using AI tools and software to develop and manage generative AI projects effectively.
Job Opportunities on Generative AI
- AI Research Scientist – Conducts research to develop new generative models and improve existing ones.
- Machine Learning Engineer – Designs and builds machine learning models, including generative AI systems, for various applications.
- Data Scientist – Analyzes and interprets complex data to develop generative AI solutions and derive actionable insights.
- AI Developer – Creates and implements AI solutions and applications using generative models for tasks like text and image generation.
- Computer Vision Engineer – Focuses on developing generative models for image and video synthesis and analysis.
- Natural Language Processing (NLP) Engineer – Works on generative models for text generation, language understanding, and conversational AI.
- Product Manager for AI – Oversees the development and deployment of AI products, including those using generative technologies.
- AI Consultant – Advises businesses on implementing generative AI solutions to solve specific problems and enhance processes.
- Ethics and Compliance Specialist – Ensures that generative AI applications are developed and used in an ethical and compliant manner.
- AI Trainer/Instructor – Provides training and education on generative AI technologies to individuals and organizations.
Generative AI Placement Program
Generative AI Masters Institute offers a comprehensive placement program designed to support students of its Generative AI training in securing rewarding job opportunities. The program includes personalized career counseling, resume building, and interview preparation to help candidates effectively showcase their skills to potential employers.
The placement program also features job fairs, recruitment drives, and networking events where students can meet with recruiters and industry professionals. With a focus on aligning individual career goals with market opportunities.
Generative AI Institute aims to ensure that graduates are well-prepared to enter the competitive field of generative AI and advance their careers.
Generative AI Placement Program
Intensive 3-Month Curriculum: Engage in a rigorous, hands-on training program complete with assignments and tasks designed to build deep expertise.
Comprehensive Project Execution: Gain real-time experience by implementing end-to-end projects that mirror industry practices.
Capstone Projects: Work on multiple capstone projects to solidify your skills and showcase your capabilities in Generative AI.
Practical Work Experience: Acquire hands-on experience that prepares you for the challenges of a professional environment.
Interview Preparation: Receive expert guidance to excel in job interviews, with focused preparation on key topics and scenarios.
Simulated Work Environment: Immerse yourself in a realistic work environment that prepares you for the demands of the industry.
With this comprehensive program, you’ll be well-equipped to secure a top-tier position in the competitive job market.
Generative AI Training In Hyderabad
5000+ jobs Opening for Generative Ai
Pre-requisites to attend Generative AI Course Online
- Basic understanding of programming languages like Python is required for developing and implementing AI models.
- Knowing the basic ideas in machine learning and statistics will help you understand advanced generative AI topics.
- Knowledge of linear algebra and calculus is beneficial for understanding the mathematical foundations of generative models.
- Prior experience with data manipulation and analysis tools will aid in working with real-world datasets effectively.
Generative AI Market Trends
- Generative AI is rapidly growing in popularity due to its ability to create unique and realistic content across various mediums.
- The technology is increasingly being adopted in industries like entertainment, design, and marketing for content generation and customization.
- Advances in generative models, such as GANs and Transformers, are driving innovation and expanding the capabilities of AI.
- There is a rising demand for generative AI in sectors like healthcare for drug discovery and simulation of medical scenarios.
- Companies are investing heavily in generative AI to enhance automation and improve efficiency in creative processes.
- Generative AI is becoming more accessible with the development of user-friendly tools and platforms.
- Ethical considerations and discussions about the implications of AI-generated content are gaining more attention as the technology advances.
- The market for generative AI is expected to continue growing, with increased applications in both consumer and enterprise solutions.
- The growth of generative AI is creating new job opportunities in fields like AI research, data science, and machine learning engineering.
- There is a rising demand for professionals skilled in generative AI to develop, implement, and manage AI-driven solutions across various industries.
- Prompt engineering is the process of crafting inputs to effectively guide generative AI in producing accurate and relevant outputs
Generative AI Masters achievements
Our Great Achievements
Generative AI Learners Testimonials
Highlights Of Generative AI Course
- The Generative AI course by Generative AI Masters is designed to provide a comprehensive understanding of generative AI technologies.
- The course covers key topics like machine learning, deep learning, natural language processing, and AI ethics.
- Students will learn how to build and deploy generative AI models for various applications, including text, image, and audio generation.
- The curriculum includes hands-on projects and real-world case studies to enhance practical skills.
- We at Generative AI Masters has the most experienced instructors who are industry experts with extensive knowledge in Generative AI.
- The course is suitable for beginners as well as professionals looking to upskill in generative AI.
- Online and flexible learning options are available to accommodate different learning schedules.
- Students will gain access to exclusive AI tools and resources provided by us at Generative AI Masters.
- The institute provides career support and networking opportunities to help students advance in the AI field.
- Upon completion, students receive a certification from Generative AI Masters, recognized by leading tech companies.
- Covers the important modules like MLOPS that can help you in the real time work environment while executing a project.
Generative AI Masters Course Outline
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Certification
- Google Cloud Professional Data Engineer – Includes coverage of machine learning and AI technologies, including generative models.
- Deep Learning Specialization by Coursera – Offered by Andrew Ng, this specialization covers key aspects of deep learning, including generative models.
- Machine Learning and AI Foundations by Microsoft – Provides foundational knowledge in AI, including applications of generative AI.
- Generative Adversarial Networks (GANs) Specialization by Udacity – Focuses specifically on GANs, a major technology in generative AI.
- M AI Engineering Professional Certificate – Covers various AI technologies and includes aspects of generative AI in its curriculum.
- NVIDIA Deep Learning Institute Certifications – Offers certifications in deep learning and AI, including generative techniques.
- Stanford University’s Machine Learning Certificate – Includes coursework on machine learning techniques relevant to generative models.
Faqs
Generative AI refers to a type of artificial intelligence that creates new and original content, such as text, images, or music, using advanced algorithms and models.
Basic programming skills, familiarity with machine learning concepts, and knowledge of linear algebra and calculus are recommended for the training.
The training covers fundamental concepts of generative AI, deep learning models, GANs, Transformers, practical applications, and ethical considerations.
Training is offered through various modes including classroom sessions, self-paced online videos, and corporate training programs.
Tools such as TensorFlow, PyTorch, Keras, Hugging Face Transformers, and Google Colab are used during the training.
The duration varies depending on the mode of training, typically ranging from a few weeks to several months.
Yes, upon successful completion of the training, participants receive a certification from Generative AI Masters that is recognized in the industry.
Career support includes resume building, interview preparation, job placement assistance, and networking opportunities with industry professionals.
Yes, the training includes practical projects and real-world case studies to help you apply the concepts learned and gain hands-on experience.
You can enroll by contacting us on the Gen AI Masters website, choosing your preferred mode of training, and following the registration process provided.