Instructor-led Generative AI for Software Developers live Online Training Schedule

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40,000.00 Duration: 60 Hours
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About your Generative AI for Software Developers Training

Skills Covered

Building and training generative models
Implementing GANs, VAEs, and GPT
Model optimization and performance improvement
Deploying and integrating generative AI applications

Tools Covered

Python programming language
AI frameworks and libraries (TensorFlow, PyTorch, Keras)
Development environments (Jupyter Notebook, PyCharm)
Cloud platforms (AWS, Azure, GCP)

Generative AI for Software Developers Training Syllabus

Curriculum Designed by Experts

Introduction to Generative AI
Topics
  • What is Generative AI?
  • History and Evolution of Generative AI
  • Key Concepts and Terminology
Topics
  • Understanding Generative Adversarial Networks (GANs)
  • Variational Autoencoders (VAEs)
  • Transformer Models (GPT)
Topics
  • Installing Python and Required Libraries
  • Setting Up Development Tools and Frameworks
  • Working with Jupyter Notebooks
Topics
  • Implementing GANs from Scratch
  • Training and Fine-Tuning VAEs
  • Developing Applications with GPT Models
Topics
  • Text Generation and Completion
  • Image Synthesis and Manipulation
  • Music and Audio Generation
  • Code Generation and Assistance
Topics
  • Improving Model Performance
  • Handling Large Datasets
  • Transfer Learning and Pre-trained Models
Topics
  • Deploying Models on Cloud Platforms
  • Integrating Generative AI into Existing Applications
  • Building APIs for Generative Models
Topics
  • Ethics in Generative AI
  • Addressing Bias and Fairness
  • Ensuring Data Privacy and Security

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Why Generative AI for Software Developers Training From Xpertised Learning

Live Interactive Classes

  • Top-Tier Trainers
  • Real Time Guidance by Industrial Experts
  • In Class Doubt Clearance

Resource Access

  • Life Time Access to Resource Library

Support

  • One-to-One Lab and Training Assistance
  • Help Desk Support
  • Doubt Clearance in Real-time

Project Based Learning

  • Labs and Learning Based from Industrial Experts
  • Learning Based on Project Scenarios

Certification

  • Xpertised Learning Training Certificate
  • Certificate of Completion

Labs

  • Cloud based Labs *Labs based on course requirement only

Generative AI for Software Developers Training Details

This course provides a deep dive into generative AI, focusing on its principles, methodologies, and practical applications. Participants will learn how to build and deploy generative AI models, such as GPT and GANs, and understand their use cases in various domains. The course emphasizes hands-on projects and real-world applications.

  • Develop specialized skills in generative AI, enhancing your ability to create innovative AI-driven software solutions.
  • Boost your career prospects by mastering generative AI, making you an attractive candidate for roles in AI development and research.
  • Stay ahead in the tech industry by acquiring expertise in generative AI, ensuring your ability to leverage cutting-edge technology in software development.
  • Comprehensive understanding of generative AI.
  • Hands-on experience with real-world projects.
  • Enhanced problem-solving and development skills.
  • Access to a community of AI professionals and experts.
  • Building and training generative models
  • Implementing GANs, VAEs, and GPT
  • Model optimization and performance improvement
  • Deploying and integrating generative AI applications
  • Python programming language
  • AI frameworks and libraries (TensorFlow, PyTorch, Keras)
  • Development environments (Jupyter Notebook, PyCharm)
  • Cloud platforms (AWS, Azure, GCP)
  • Understand the core concepts and techniques of generative AI.
  • Develop and deploy generative AI models.
  • Apply generative AI to solve real-world problems.
  • Address ethical considerations in the development and deployment of AI models.
  • Software Developers
  • Data Scientists
  • AI Enthusiasts
  • IT Professionals
  • Anyone interested in generative AI technologies
  • Basic knowledge of programming (Python preferred)
  • Familiarity with machine learning concepts
  • Fundamental and advanced concepts of generative AI
  • Practical skills in building and deploying generative models
  • Applying generative AI to real-world applications
  • Ethical considerations and best practices in AI development
  • A computer with an internet connection
  • Python and related libraries installed
  • IDEs like Jupyter Notebook or PyCharm
  • AI Developer
  • Machine Learning Engineer
  • Software Developer
  • Data Scientist
  • AI Consultant

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