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Generative AI Course, Generative AI Training from Apponix Academy

This program equips you with the knowledge and skills needed to excel in the field of Generative AI. Gain practical insights and industry expertise to confidently develop, implement, and innovate with AI-driven solutions.


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Skills Covered in Generative AI Course

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Generative Models&Advanced Model Architectures
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Large Language Models (LLMs) & Foundation Models
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Computer Vision & Image/Video Generation
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Advanced NLP & Language Modelling
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Responsible AI & Ethics
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AI Infrastructure & Deployment
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AI Tooling & Frameworks
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Speech & Audio Synthesis& Multimodal AI
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Cutting-Edge Computer Vision & Video Generation
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Autonomous AI & Agentic Workflows
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Industry-Ready AI Infrastructure & Optimization
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GenAI for Enterprise Applications
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Advanced Data Engineering for GenAI
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AI Security & Ethical Considerations
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Real-Time AI & Edge Computing
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The Future of Generative AI & Next-Gen Technologies

Key Features in Generative AI Course

Generative AI & Large Language Models (LLMs)
Prompt Engineering & AI Fine-Tuning
Machine Learning & NLP
Computer Vision & AI for Video/Image Processing
AI in Education & LMS Development
AI & Data Science Training
Industry & Academic Research
AI Deployment &MLOps
Cloud AI Services

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Generative AI Course Reviews


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Generative AI Course Syllabus

Prerequisites

Generative AI requires a strong foundation in machine learning, deep learning, and data processing techniques. Understanding neural networks, probability, and optimization methods is essential for developing and fine-tuning models.

Generative AI Course Course Syllabus

MODULE 1: Python Basics & Core Programming
Introduction to Python
  • What is Python?
  • Installation & Setup (Anaconda, Jupyter Notebook, VS Code)
  • Running Python Programs (Interactive & Script Mode)
Python Fundamentals
  • Variables & Data Types
  • Operators (Arithmetic, Logical, Relational)
  • Conditional Statements (if-else)
  • Loops (for, while)
  • Functions (Types, Arguments, Lambda Functions)
Data Structures in Python
  • Strings: Operations, Slicing, Methods
  • Lists: Accessing, Modifying, Methods, List Comprehensions
  • Dictionaries: Key-Value Pairs, Operations
  • Sets: Set Operations, Built-in Functions
Object-Oriented Programming
  • Classes & Objects
  • Inheritance & Polymorphism
  • Encapsulation & Data Hiding
MODULE 2: Python for Data Science
Working with Files & Exception Handling
  • File Handling (Read, Write, Append)
  • Exception Handling (try-except, finally)
NumPy for Data Manipulation
  • Arrays vs Lists
  • Creating & Modifying Arrays
  • Array Indexing & Slicing
  • Mathematical Operations
Pandas for Data Handling
  • DataFrames & Series
  • Importing Datasets (CSV, JSON, Excel)
  • Data Cleaning & Handling Missing Data

 

Data Visualization using Matplotlib & Seaborn
  • Line Charts, Bar Graphs, Pie Charts
  • Histograms, Scatter Plots, Heatmaps
MODULE 3: AI & Machine Learning
Introduction to AI & ML
  • AI vs ML vs Deep Learning
  • Supervised vs Unsupervised Learning
  • Real-World Applications
Supervised Learning Algorithms
  • Linear & Logistic Regression
  • Decision Trees & Random Forest
  • Support Vector Machines (SVM)
  • Naïve Bayes Classifier
Unsupervised Learning Algorithms
  • K-Means Clustering
  • Hierarchical Clustering
  • Principal Component Analysis (PCA)
Deep Learning with TensorFlow & Keras
  • Introduction to Neural Networks
  • Activation Functions
  • Building Artificial Neural Networks (ANN)
  • Convolutional Neural Networks (CNN)
  • Recurrent Neural Networks (RNN)
Natural Language Processing (NLP)
  • Text Preprocessing (Tokenization, Lemmatization)
  • Bag of Words & TF-IDF
  • Named Entity Recognition (NER)
  • Sentiment Analysis
Reinforcement Learning
  • Agents & Environment
  • Q-Learning Algorithm
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Projects / Assignments covered

Project 1

AI-Powered Medical Report Summarization & Diagnosis Assistant

An advanced AI assistant that extracts key insights from medical reports, summarizes critical information and provides preliminary diagnostic suggestions to enhance decision-making for doctors and patients.

Project 2

Personalized AI Shopping Assistant (LLM + RAG + Vision AI)

A next-gen shopping assistant that leverages LLMs, Retrieval-Augmented Generation (RAG), and Vision AI to offer personalized product recommendations, price comparisons, and visual search for an enhanced e-commerce experience.

Project 3

Generative AI-Based Video Editing & Captioning (Gen-3, Stable Diffusion)

A cutting-edge AI-powered tool that uses Gen-3 models and Stable Diffusion to automate video editing, generate high-quality captions, and enhance content creation with minimal manual effort.

Our Top Instructors

Overview of Generative AI Course

  • Generative AI Certification Training is a comprehensive program designed to help professionals gain expertise in AI-driven content generation and machine learning models.
  • The training is aimed at individuals who want to enhance their skills in artificial intelligence and demonstrate their expertise in generative AI to potential employers.
  • Our training program is led by experienced trainers with deep knowledge of AI, equipping you with the latest skills, tools, and best practices in the industry.
  • With our Generative AI certification training, you will learn how to design, train, and deploy AI models for text, image, and content generation using advanced machine learning techniques.
  • Upon completion of the training, you will be well-prepared to take the certification exam and earn a credential that showcases your proficiency in generative AI.

Benefits of learning Generative AI

Learning Generative AI equips you with cutting-edge skills in AI-powered tools like

  • Master In-Demand AI Skills – Gain expertise in ChatGPT, Gemini, Llama, Stable Diffusion, AI coding, and automation.
  • Unlock High-Paying Jobs – Qualify for AI/ML roles at top companies like Google, Microsoft, and OpenAI.
  • Gain Hands-On Experience – Build AI applications, chatbots, and automation tools with real-world projects.
  • Future-Proof Your Career – Stay ahead of AI disruptions by mastering fine-tuning, RAG, and AI deployment.
  • Boost Professional Credibility – Earn a globally recognized certification to enhance your resume and job prospects.


Related job roles

  •  AI & ML Core: AI Engineer, Data Scientist, Prompt Engineer, LLM Engineer
  • Development: AI Software Engineer, Chatbot Developer, AI Solutions Architect
  • Data & Analytics: AI Data Engineer, AI-Powered Data Analyst, BI Analyst
  • Content & Design: AI Content Creator, Digital Artist, Video/Image Specialist
  • Industry-Specific: AI Consultant (Healthcare, Finance), Cybersecurity Engineer
  • Leadership: AI Ethics Consultant, AI Evangelist, Chief AI Officer (CAIO)

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3000+ Learners

Generative AI Exam & Certification

Generative AI is a type of artificial intelligence that can create new content, like text, images, videos, and music, based on the data it has learned from. It works like a smart assistant that can generate creative and useful outputs.

It uses advanced machine learning models, like deep learning and neural networks, to understand patterns in data. Then, it creates new content by predicting what comes next, similar to how a person might complete a sentence or draw a picture.

Generative AI is used for:

  • Creating images, videos, and music
  • Writing articles, stories, or summaries
  • Generating realistic chat responses (like ChatGPT)
  • Enhancing video editing and animation
  • Designing personalized products and advertisements

No, Generative AI can assist and enhance creativity, but it still relies on human input and guidance. It can help speed up tasks, generate ideas, and automate repetitive work, but humans are needed for originality, emotions, and final decision-making.

Generative AI is generally safe, but it depends on how it is used. Some risks include misinformation, deepfakes, and biased outputs. To ensure safe use, it’s important to verify AI-generated content and use it responsibly.

Certification

Career after Generative AI Course

Career Opportunities After Generative AI Course

If you're considering taking a Generative AI certification course, you may be wondering what career opportunities are available once you've completed the training. Generative AI is one of the most in-demand fields in artificial intelligence, offering a wide range of job opportunities for professionals with expertise in this domain. Here are some potential career paths for Generative AI professionals:

  • AI Research Scientist – AI research scientists work on developing and improving generative models, conducting research on deep learning, and contributing to AI advancements.

  • Machine Learning Engineer – Machine learning engineers design, train, and deploy generative AI models for text, image, and video generation using frameworks like TensorFlow and PyTorch.

  • AI Product Manager – AI product managers oversee the development and deployment of AI-driven solutions, ensuring that generative AI models align with business needs.

  • Data Scientist – Data scientists use generative AI techniques to analyze data, build predictive models, and develop AI-powered analytics solutions.

  • Deep Learning Engineer – Deep learning engineers specialize in building, optimizing, and fine-tuning advanced neural networks for generative AI applications.

  • AI Consultant – AI consultants help businesses integrate generative AI into their products and services, offering technical expertise and strategic guidance.

Overall, a Generative AI certification can open doors to a variety of exciting career opportunities in artificial intelligence. With the rapid growth of AI-driven applications, now is the perfect time to pursue a Generative AI certification and take your career to the next level.

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Frequently Asked Questions

Generative AI is a subset of artificial intelligence that creates new content, such as text, images, audio, and code. It is widely used in automation, creativity, and decision-making applications.

This course is designed for beginners, AI enthusiasts, professionals, and students who want to explore the world of AI-driven content generation.

While prior experience in programming and machine learning is helpful, it is not mandatory. The course starts with fundamental concepts.

You will learn about deep learning models, transformer architectures, NLP, image generation, AI ethics, and real-world applications.

Yes! The course covers AI basics before progressing to advanced Generative AI concepts, making it accessible to all learners.

The course includes practical training with OpenAI’s GPT, DALL·E, TensorFlow, PyTorch, and cloud-based AI services.

It includes interactive lectures, hands-on projects, real-world case studies, and assessments to reinforce learning.

Yes, a recognized certificate will be provided after successfully completing the training.

You can pursue roles such as AI Developer, Machine Learning Engineer, Data Scientist, and AI Consultant.

You can register online via our website or contact our admissions team for assistance.

 

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Why GenAI is more Popular?

Job Opportunities for GenAI Professionals in 2025

  • Generative AI Engineer: A rapidly growing role with approximately 3,000 job openings and a significant demand for skills in creating AI-generated content and solutions1.
  • AI Research Engineer: This role is expected to see around 2,000 job openings, focusing on advancing AI technologies through research and development1.
  • Data Scientist (AI Applications): With about 5,000 openings, data scientists are increasingly sought after for their ability to analyze data and implement AI solutions across various sectors1.
  • AI Product Manager: This role requires a blend of technical and business skills, with around 1,000 job openings available for professionals who can manage AI product lifecycles effectively1.
  • Machine Learning Engineer: The most in-demand position, boasting 16,000 job openings and an average salary of $161K annually, highlighting the critical need for expertise in machine learning12.
  • Robotics Engineer (AI Focus): This role is gaining traction with approximately 55.6K monthly searches, indicating robust interest in integrating AI with robotics1.
  • Deep Learning Specialist: With 19,000 job openings and an average salary of $119.1K, deep learning specialists are vital for developing advanced AI systems1.
  • Natural Language Processing (NLP) Engineer: This role ranks fifth in demand with 6,000 job openings and a lucrative average salary of $156K, focusing on AI's ability to understand human language1.
  • AI Ethics Specialist: As businesses increasingly adopt AI technologies, there is a growing need for professionals who can address ethical concerns related to AI deployment2.
  • Synthetic Data Engineer: Emerging as a new role, synthetic data engineers create artificial datasets to train AI models without compromising privacy or security3.
  • AI Strategy Consultant: Professionals in this role help organizations align their AI initiatives with business goals, ensuring effective integration of AI technologies2.
  • Generative AI Research Scientist: This position focuses on exploring new applications of generative AI and is expected to grow significantly as the technology evolves34.

 Why should you take GenAI?

  1. Career Advancement
    • Directly relevant to high-demand roles.
    • Future-proofs your skills.
    • Increased earning potential.
  2. Powering Up Your Existing Role
    • Enhanced content creation.
    • Automation of repetitive tasks.
    • Idea generation and brainstorming.
  3. Personal Enrichment & Creative Expression
    • Bringing creative visions to life.
    • Learning as a hobby/passion.
    • Staying ahead of the curve.
  4. Specific Industries & Applications
    • Healthcare (drug discovery, personalized medicine).
    • Finance (fraud detection, risk assessment).
    • Manufacturing (predictive maintenance, product design).
    • Gaming (realistic environments, character dialogue).

Professional Experience

 Master Trainer & SME (GenAI, AI-ML, Data Science) |

  • Leading AI-driven curriculum design and training programs for students and professionals.
  • Conducting hands-on AI workshops for business professionals and engineering graduates.
  • Mentoring students on AI projects, helping them secure international internships.

 Project Manager | AI-Based LMS for Indian Railways

  • Managing AI development for personalized learning, mock tests, and AI-driven performance analysis.
  • Overseeing AI modules for voice-to-text, translation, and smart content generation.

 Research Collaborator & Honorary Scientist | Global Universities & Institutes

  • Collaborating with IITs, Wrocław University (Poland), University of South Wales, and Lincoln University College on AI applications in Healthcare, Power Systems, and Neuroscience.
  • Leading AI-driven medical research in predictive analytics and healthcare informatics.

 Industry & Academic Recognition

  • Best Teacher Award – ITM (SLS) Baroda University
  • Certificate of Excellence in AI in Neuroscience – Shiraz University of Medical Sciences, Iran
  • Adjunct Honorary Scientist – IBCR (India), Genius Singulars (India)
  • Hon. Sr. Fellow – WIDI, University of South Wales

Global Research & Training Collaborations

  • India: Research collaborations with IIT Dhanbad, IIT Indore, and Pune University.
  • Poland: AI & ML in Power Systems (Wroclaw University of Science & Technology).
  • Malaysia: AI & Data Analytics with Lincoln University College & Xiamen University.
  • Vietnam: AI-driven Medical Informatics with Thu Dau Mot University.
  • UK: AI & Data Science Internships with the University of West London.

Technical & AI Training

  • Corporate AI Workshops: AI for Business Decision-Making, GenAI in Marketing, AI for HR.
  • University-Level AI Training: AI & ML for Engineering, Data Science, and Healthcare Applications.
  • GenAI Bootcamps: LLMs, Prompt Engineering, AI for Content Generation, AI Video Synthesis.
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