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GEN AI

Master Generative AI

Advanced Certification Programme in AI, ML, Data Science, and Generative AI

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Hands On Project

Implement your learning through real world project

Duration

75 days of comprehensive training

Customized Learning

Online offline mode available on weekday and weekend batches

COURSE OVERVIEW

 

This course provides a deep dive into the fundamentals and advanced concepts of Artificial Intelligence (AI), Machine Learning(ML), Data Science, and Generative AI. From understanding the basics to implementing complex algorithms, this course covers everything you need to know to excel in these fields.Entire course will be driven by Gen AI tools like cody, codegpt, copilot, gemni pro..etc.


  • Introduction
  • Python and AI/ML Basics
  • Data Preparation & Augmentation
  • Model Selection & Architecture Design
  • Training, Evaluation, & Fine-tuning
  • Generation, Integration, & Testing
  • Deployment, Monitoring, & Maintenance
  • Course Overview & Importance of AI/ML
  • GenAI Structure and Goals
  • What is AI, ML, Data Science, and Generative AI?
  • History and evolution of AI, ML, and Generative AI.
  • Importance and applications of AI, ML, Data Science, and Generative AI in various industries.
  • Python Basics for AI/ML
  •  Introduction to NumPy, Pandas, Matplotlib,scikit-learn
  • Deep Learning with PyTorch.
  •  Overview of AI/ML Fundamentals
  • Fundamentals of AI & ML
  • Overview of supervised, unsupervised, and reinforcement learning.
  • Understanding algorithms: decision trees, linear regression, logistic regression, etc.
  • Deep Learning for Generative AI The GenAI Tech Stack
  • Ethical Considerations in GenAI
  • Python Modules (NumPy, Pandas, Matplotlib)
  •  TorchText and Hugging Face Transformers
  •  PyTorch Core Library (torch, nn, optim, utils, nn.functional)
  • Data cleaning, transformation, and normalization.
  • Handling missing data and outliers.
  • Feature selection and extraction.
  • Data Preprocessing with Python and PyTorch.
  • Prompt Engineering with Google AI Tools
  • Data Quality Assurance & OpenAI File Formats
  • Data visualization tools and techniques.
  • Exploratory Data Analysis (EDA).
  • Communicating insights from data.
  • Deep Dive into Generative AI Models in PyTorch
  • Architecting for Prompt-based Language Models
  • Deep Learning Algorithms for Text Generation
  • Deep learning fundamentals: neural networks, CNNs, RNNs.
  • Natural Language Processing (NLP) and its applications.
  • Model Selection & Use Case Mapping
  • LLMOps on Google Cloud with Python & PyTorch
  • Mastering Machine Learning Frameworks
  • Leveraging Introduction to Generative AI and its applications.
  • Generative models: GANs, VAEs, etc.
  • Creating art, music, and text with Generative AI.
  • Introduction to Large Language Models (LLMs) and their applications.
  •  Retrieval-Augmented Generation (RAG) models and their use cases.
  • 4Prompt engineering techniques for improving LLM performance.
  • OpenAI API & Fine-tuning Techniques
  • Understanding & Implementing Optimization Algorithms
  • Model Evaluation & Performance
  • Metrics Fine-tuning based on Evaluation
  • Generative Model Integration with Applications
  • Testing & Validation of Generated Text Content
  • Advanced Prompt Engineering for Control
  • Production-Ready Deployment on Google Cloud
  • LLMOps Monitoring & Bias Detection
  • Continuous Maintenance & Model Improvement

ADDITIONAL RESOURCES

 

We Encourage students to work on real-world projects and participate in hands-on workshops to apply their learning and reinforce theoretical concepts.


Hands-on Workshops

We Believe “Knowledge sharing is caring ”

Average package of course (Generative AI)

30%

Average salary hike

9Lac

Average Package

Instructor details:

Srinivas

Corporate Trainer, Speaker
Meet Srinivas, an experienced professional with 17 years in the industry and 8 years of training expertise. He has helped over 2000 IT professionals succeed.

Success Stories

Jeswanth

IT Professional, Mumbai, India > Bangalore, India
This course exceeded my expectations! The hands-on projects were incredibly engaging, helping me grasp complex DevOps concepts with ease. With supportive instructors and practical learning, I feel well-prepared for real-world challenges in IT.

Our Students' Feedback

The success stories of our students are a testament to the quality of education at Tekspot.
Hear directly from those who have experienced our courses and transformed their careers.

DevOps is a software development approach that combines software development (Dev) with IT operations (Ops). It aims to shorten the development lifecycle, increase deployment frequency, and deliver high-quality software. DevOps is important as it improves collaboration between development and operations teams, accelerates delivery, and enhances overall software quality.

This course is suitable for beginners interested in learning DevOps principles and practices, as well as IT professionals looking to enhance their skills and advance their careers in DevOps roles.
There are no specific prerequisites for enrolling in this course. Basic knowledge of programming and familiarity with IT concepts would be beneficial but not mandatory.

Yes, the course includes hands-on projects and practical exercises to reinforce learning and provide real-world experience in DevOps workflows.

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Described Above. Please scroll up to find it.

Our Students' Feedback

The success stories of our students are a testament to the quality of education at Tekspot.
Hear directly from those who have experienced our courses and transformed their careers.