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Generative AI SPECIALIZATION  Course  

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Perks of the Generative AI Specialization Course

Program Overview

overview
The Generative AI Specialization provides a comprehensive journey into creating advanced generative AI models. Beginning with Python, you will learn to build and fine-tune large language models (LLMs) and multimodal AI systems. Throughout the course, you will explore key generative AI models like Llama2 and Stable Diffusion, and understand how to leverage AI frameworks such as PyTorch and LangChain for efficient development. You’ll also dive into tools like LoRA and Retrieval-Augmented Generation (RAG), and work with AI-focused databases including Pinecone, FAISS, and ChromaDB. By the end of the program, you will be fully equipped to develop, optimize, and deploy cutting-edge generative AI models for a variety of practical applications.

Who Is This Program For?

The Generative AI Specialization is designed for a wide range of professionals and enthusiasts who are eager to dive into the world of advanced AI technologies. This program is ideal for:

Course learning objectives

By the end of the Generative AI Specialization course, learners will be able to:

Skills you'll gain

Python Programming
Statistics and Probability
Calculus for AI
Vector Algebra
Transformer Models
Natural Language Processing (NLP)
GPT Architecture
Neural Networks (MLP, CNN, RNN)
Diffusion Models
Large Language Models (LLMs)
Model Fine-Tuning (LoRA, RAG)
Generative Adversarial Networks (GANs)
Multimodal AI (Text, Image, Sound)
Vector Databases (Pinecone, FAISS, ChromaDB)
AI Frameworks and tools

PyTorch

Flexible Framework for Deep Learning

PyTorch is one of the most popular frameworks for developing deep learning models. Its dynamic nature makes it popular for research and production, helping users build neural networks for various applications like image recognition and NLP.

PyTorch

AI Architectures & Fine-Tuning

Master Advanced AI Models & Techniques

In this course, you'll explore the latest AI architectures and their fine-tuning techniques, gaining hands-on experience with state-of-the-art models used in industries such as healthcare, finance, and language generation.

LLama3

LLama3

What it is

LLaMA3 is Meta’s newest language model designed for long-form text generation, translation, and NLP tasks. It supports over 30 languages and has been trained on 15 trillion tokens, making it more efficient and accurate than its predecessor​.

Fine-Tuning

With LoRA (Low-Rank Adaptation) and RAG (Retrieval-Augmented Generation), LLaMA3 can be fine-tuned to respond with greater relevance and efficiency, using fewer computational resources.

Applications

Used in NLP tasks like chatbots, language translation, and text summarization.

Mistral

Mistral

What it is

Mistral is optimized for domain-specific tasks in industries like finance and healthcare, where precision is crucial. Its specialized fine-tuning capabilities make it adaptable to smaller, more niche applications.

Fine-Tuning

Mistral uses LoRA to minimize computational resources while enhancing its domain-specific outputs.

Applications

Ideal for medical diagnoses, financial risk assessments, and other specialized tasks.

Gemini

Gemini

What it is

Gemini is an emerging model from Google DeepMind, offering advanced capabilities in both multimodal and language-based tasks. It integrates vision, language, and reasoning into one model, allowing it to excel in tasks like image understanding alongside text generation.

Fine-Tuning

Mistral uses LoRA to minimize computational resources while enhancing its domain-specific outputs.

Applications

Creative content generation, autonomous agents, and complex decision-making systems.

Fine-Tuning Techniques Explained

LoRA (Low-Rank Adaptation)

LoRA (Low-Rank Adaptation)

What it is

LoRA fine-tunes large models by focusing on specific layers, reducing training time and resources. This technique allows for faster, more efficient fine-tuning of massive models like LLaMA3 and Gemini.

Fine-Tuning

Why it matters: LoRA is perfect for businesses looking to fine-tune AI models with limited resources, making the technology more accessible.

RAG (Retrieval-Augmented Generation)

RAG (Retrieval-Augmented Generation)

What it is

RAG improves AI model outputs by retrieving relevant information from external sources. This makes the model more contextually aware, resulting in higher-quality answers and responses.

Fine-Tuning

Why it matters: It’s ideal for customer service, research, and other applications where up-to-date information is crucial.

roadmap

Course Curriculum

Industry recognized training Certificate
Upon completing our course, you will receive an industry-recognized training certificate, one of its biggest benefits. Use it to seek your fair share of a salary rise and demonstrate your newly acquired competence to your employer!
data analytics for ai certificate

What Sets Us Apart?

FeatureOur ProgramOther Courses
Expert-Led Sessions 24 weeks of instruction from top-tier professionals with industry experience Often lack guidance from seasoned experts, relying on less experienced instructors
Flexible Learning Options Accessible 24/7 with over 150 hours of on-demand content Limited accessibility and rigid learning schedules
Practical Assessments 15 practical assessments for hands-on practice Minimal practical exposure and hands-on opportunities
Real-World Assignments Engage in 14+ real-world assignments directly linked to industry challenges Minimal practical exposure and hands-on opportunities
Live Doubt-Clearing Sessions 11 live sessions with experts for doubt resolution Limited opportunities for real-time support and query resolution
Capstone Projects 2-3 capstone projects applying skills to real-world problems Few or no chances to work on substantial, real-world projects
Live Interviews 5 mock interviews to prepare you for the real world Lack of structured live interview preparation
Mock Interviews 10 mock interviews to prepare for real job scenarios Lack of structured mock interview preparation
Career and Placement Support Comprehensive support for job placements, including resume reviews and salary negotiation tips Often lack continuous support for career advancement and placement
Fee Structure
We provide a really competitive rate in the market as the best data analytics training institute in Gurgaon. Our course fee for the entire course is:
One-Time Payment with Placement Assurance.
  • Refund of up to 70% if you don’t get placed within 10 months (maximum refund ₹49,000).

Additional Benefits:

  • Job Assistance: Our program ensures support until you secure a role. 100% Placement Program: We are fully committed to helping you find the right opportunity.
  • Real-World Projects: Gain hands-on experience with projects based on real industry scenarios.
  • Comprehensive Curriculum: Gain expertise in generative AI across text, image, and audio applications, including multimodal AI.
One-time Payment
₹80,000

Testimonials of our Successful Learners

What our learners have to say

"Enrolling in this full stack data science course was one of the best decisions I’ve made for my career. The curriculum is well-structured, starting with foundational Python and progressing through complex topics like deep learning and Kafka. The placement assistance was excellent, and I landed a job as a data scientist within a few months of completing the course. I highly recommend this program to anyone serious about building a career in data science."
Aditi Sharma
Data Scientist
School of Core AI
"The course provided a comprehensive overview of the entire data science pipeline, from Python programming to advanced deep learning techniques. The real-time project training was a game-changer, giving me practical experience that I could showcase to potential employers. Thanks to the 100% placement assistance, I was able to transition smoothly into a data analyst role at a reputed firm. This course is an excellent investment in your future."
Ravi Patel
Data Analyst
School of Core AI
"I was initially hesitant to enroll in the course, but it exceeded all my expectations. The focus on both SQL and MongoDB provided me with a solid understanding of different database technologies. The statistical analysis and EDA sections were particularly insightful, equipping me with skills to interpret and analyze data effectively. The course's project-based approach allowed me to gain practical experience, and the placement support helped me secure a role as a machine learning engineer. This course is perfect for anyone looking to enter the data science field with confidence."
Neha Gupta
Machine Learning Engineer
School of Core AI
"This full stack data science course offered an in-depth exploration of both the theoretical and practical aspects of data science. The training on web frameworks and Docker was especially useful, as it helped me understand how to deploy and manage data science applications effectively. The course's well-rounded curriculum prepared me for various challenges in the field, and the support provided during the job search was invaluable. I am now working as a data engineer, and I owe a lot of my success to this program."
Arjun Singh
Data Engineer
School of Core AI
"From mastering Excel and SQL to diving into advanced machine learning and NLP, each module was meticulously designed to build upon the previous one. The real-time project work allowed me to develop a strong portfolio, and the placement assistance team was dedicated to helping me find the right job match. I am now thriving as a data scientist, thanks to the skills and knowledge I gained from this course."
Sanya Mehta
Data Scientist
School of Core AI
"The full stack data science course was a transformative experience for me. The practical approach of integrating theory with real-world projects made learning engaging and effective. The section on Redis and Kafka was particularly insightful, providing me with crucial knowledge for managing data pipelines and real-time data processing. The placement assistance was exceptional, and I was able to secure a position at a top tech company soon after completing the course. I highly recommend this course to anyone looking to make a mark in data science."
Vikram Rao
Data Scientist
School of Core AI
"This course offered a thorough and practical education in data science, covering everything from Python basics to advanced deep learning techniques. The instructors were experienced and provided valuable insights throughout the course. The projects and real-time training were instrumental in helping me apply my knowledge. With the support of the placement team, I successfully transitioned into a data analyst role at a well-known firm. The skills and experience gained from this course have been invaluable to my career growth."
Kavita Joshi
Data Analyst
School of Core AI
"The full stack data science course provided a comprehensive learning experience with a well-rounded curriculum. I particularly enjoyed the modules on statistical analysis and exploratory data analysis, which were critical in developing my data analysis skills. The hands-on projects and real-time training helped me build a strong portfolio. The placement assistance was effective in helping me find a suitable job in the data science field."
Manoj Kumar
Data Analyst
School of Core AI
"The course exceeded my expectations in terms of content and instruction. The detailed coverage of both SQL and MongoDB, combined with practical training on web frameworks and Docker, provided a robust foundation for my data science career. The placement assistance was thorough, and I appreciated the personalized support in finding job opportunities. I am now working as a data scientist and credit much of my success to the skills and knowledge I gained from this program. It’s a fantastic course for anyone serious about data science."
Shruti Patel
Data Scientist
School of Core AI
"I found this course to be exceptionally well-structured and comprehensive. The blend of theoretical knowledge and practical experience, especially with technologies like Redis and Kafka, prepared me well for the real-world challenges in data science. The project-based approach allowed me to gain hands-on experience, and the placement assistance team was highly supportive throughout the job search process. I am now employed as a data scientist at a leading company, and I attribute my success to the thorough training and support provided by this course."
Rajesh Nair
Data Scientist
School of Core AI

Frequently Asked Questions