Our Most Popular Generative AI Courses

Explore our top Generative AI Courses and take the first step towards career success

Our Generative AI Courses Duration And Fees

Generative AI Courses typically range from a few weeks to several months, with fees varying based on program and institution.

Program NameDurationFees
Applied Generative AI Specialization

Cohort Starts: 31 Jul, 2024

4 months$ 2,995
Generative AI for Business Transformation

Cohort Starts: 19 Aug, 2024

4 months$ 2,995
Post Graduate Program in AI and Machine Learning

Cohort Starts: 22 Aug, 2024

11 Months$ 4,300
AI & Machine Learning Bootcamp

Cohort Starts: 26 Aug, 2024

6 Months$ 10,000

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Generative AI Courses Advisors

  • Amitendra Srivastava

    Amitendra Srivastava

    Chief Data Scientist at Intelytica

    Amitendra’s expertise lies in utilizing data analysis and machine learning techniques to solve complex business problems and drive strategic decisions. As Chief Data Scientist, he leverages the power of data to create value and drive innovation.

    Twitter  LinkedIn
  • Ankit Virmani

    Ankit Virmani

    Data & ML Leader at Google

    Ankit is an ethical AI and data engineering enthusiast with 10+ years of experience at firms like Google, Amazon, and Deloitte. He serves as a member of the Forbes Technology Council, IU's Institute of Business Analytics, and AI 2030.

    Twitter  LinkedIn
  • Arijit Mitra

    Arijit Mitra

    Director and Head of Machine Learning & AI at Pegasystems

    Arijit is an engineering & product leader with expertise in building and deploying AI, NLP, GPT & LLMs at scale for Fortune 500 companies. As head of AI & ML at Pega, he owns the overall AI roadmap with a focus on AI applications across functions.

    Twitter  LinkedIn
  • Armando Galeana

    Armando Galeana

    Founder and CEO at Ubhuru Technologies

    A seasoned data science leader, with extensive experience in digital transformation. Throughout his career, Armando has leveraged his vast expertise in AI & ML to build infrastructure, create new lines of business and drive global implementations.

    Twitter  LinkedIn
  • Dr. Balasubramanian R

    Dr. Balasubramanian R

    Professor at IIT Roorkee

    Esteemed Professor at IIT Roorkee, holding a Ph.D. in Mathematics and Computer Science from IIT Madras. With over 20 years of teaching experience, he advocates the latest AI/ML and Data Analytics trends in his teachings, a valuable asset to our program.

    Twitter  LinkedIn
  • Dr. Sudeb Dasgupta

    Dr. Sudeb Dasgupta

    Professor at IIT Roorkee

    Respected Professor at IIT Roorkee, with a Ph.D. in Electronics Engineering from BHU. His deep understanding of electronics and view on leveraging Generative AI brings a unique perspective to this program

    Twitter  LinkedIn
  • Manish Anand

    Manish Anand

    CEO at iHUB DivyaSampark, IIT Roorkee

    Leading as CEO at iHUB DivyaSampark, IIT Roorkee. An alumnus of IIT Kanpur with an MBA from KAIST, Manish is a seasoned innovator, fostering technological innovation at IHUB  with a keen interest in AI & ML and analytics domain, making him an ideal advisor for our program.

    Twitter  LinkedIn
  • Raghav Goel

    Raghav Goel

    Generative AI & Data Science Consultant

    A passionate and successful corporate trainer who has delivered 150+ training sessions for corporates in India, Middle East, USA, and South East Asia for corporate clients like Publicis Sapient, KPMG, Capgemini, Coforge, ITC, DXC, Huawei, and IBM.

    Twitter  LinkedIn
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Generative AI Courses Learner's Reviews

  • Abhineet Srivastava

    Abhineet Srivastava

    Senior Manager - Analytics & Reporting

    The Machine Learning Course course was all worth it! The course content was comprehensive and updated. The journey from a Python-based approach to understanding Statistical concepts, Machine Learning, and other concepts was just incredible. Thanks to all the amazing trainers and co-learners for giving me such an enriched experience.

  • Sudipta Samanta

    Sudipta Samanta

    Technical Architect

    The courses are well-structured with self-learning, live classes, projects & assessment. The trainers are well trained, connect well with the students, and are good at resolving your questions. The Machine Learning Course content is excellent. In the DS course, for instance, they have gone through the right amount of statistics and linear algebra.

  • Janani Varun

    Janani Varun

    Consultant

    I would give a 5-star rating for Simplilearn's Machine Learning Course It helps me understand the content easily through online self-learning videos, and trainers assist us with their enriched knowledge, as well.

  • Aman Kukreti

    Aman Kukreti

    Business Process Analyst

    The Gen AI module in Simplilearn's AI/ML course was an eye-opener for me. The mentor's teaching style in the weekend sessions was spot on. While there's a lot of Gen AI content online, this module stood out for its structured approach and the mentor's interactive guidance. It made learning about AI easy, even for beginners like me.

  • Aakarshan Sharma

    Aakarshan Sharma

    Senior Engineer

    Before using it, I had very little insight into the depth of Generative AI's capabilities. Its integration into my workflow has facilitated numerous collaborations in the workplace, greatly enhancing my productivity. The generative AI module in Simplilearn's AI/ML course exceeded my expectations.

  • Lokesh Venugopal

    Lokesh Venugopal

    Business Excel Advisory Specialist

    While I've previously encountered the marvels of Generative AI, I was pleasantly surprised by the quality of content in the Generative AI module in Simplilearn's AI/ML course. It provided a comprehensive overview of AI fundamentals and principles specific to GenAI. I gained a deeper understanding of the significance of explainable AI.

  • Ashif Khan

    Ashif Khan

    Lead Consultant

    The curriculum of the Generative AI module in Simplilearn's AI ML course proved to be highly valuable. Initially, I encountered challenges with one of the projects and struggled to grasp its intricacies. Thankfully, my tutor provided invaluable guidance and support, enabling me to overcome these hurdles.

  • Elangovan Subbaiah

    Elangovan Subbaiah

    System Engineer

    Using Gen AI is already a part of my routine, and I found learning this module to be straightforward. I believe it'll be beneficial for my future projects. What really stuck with me was learning how to effectively utilize AI in various tasks.

  • Kunal Srikanth Mathew

    Kunal Srikanth Mathew

    Trading Assistant

    Coming from a background in robotics, I found the Gen AI module to be easily understandable. What I appreciated most was that the module provided a platform for me to address my doubts about Gen AI and deepen my understanding of the subject matter.

  • Somanathan c

    Somanathan c

    I already had some knowledge about Gen AI before taking the course. Overall, I found the course content to be good. What I found most beneficial was learning about certain new topics, which were explained clearly and in a way that made them easy to grasp

  • Ravi Shekhar

    Ravi Shekhar

    The Generative AI module was eye-opening, especially for someone like me with a finance background. It was fascinating to discover the wide-ranging applications of Gen AI across different fields. Throughout the course, I gained valuable knowledge about various AI trends such as Gen AI, prompt engineering, ChatGPT

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Know more about Generative AI

A brief overview of Generative AI courses

Simplilearn’s Generative AI courses, best suited for data scientists, software engineers, researchers, and AI enthusiasts, offer learners a comprehensive understanding of AI principles, techniques, and applications. These courses focus on the most in-demand skill areas in Generative AI with practical training.                                        

Some key topics included in these Gen AI courses are deep learning, practical implementation using frameworks like TensorFlow and PyTorch, and diverse applications like image and text generation. Students also learn about research trends, ethical considerations, and the responsible use of AI.

The growing need to learn Generative AI globally

Generative AI is rapidly gaining prominence for its ability to revolutionize various industries. Generative AI applications can create new and innovative content, such as realistic images, compelling text, and cutting-edge designs. 

This technology is driving advancements in industries like entertainment, marketing, and healthcare, offering unprecedented possibilities for creativity and efficiency. Enrolling in Generative AI courses is essential to keeping pace with this technological evolution. These courses teach advanced AI techniques and unlock diverse career opportunities in this growing field.

Benefits of enrolling in Generative AI courses

Generative AI tools and applications are used in numerous business models across various industry sectors. Enrolling in Generative AI courses will improve your ability to create innovative and intelligent systems to generate new content. 

These courses provide in-depth knowledge of trending AI techniques, enhance problem-solving skills, and open up career opportunities in various fields. They also foster creativity and allow for the development of personalized AI applications.

Different Generative AI certifications offered by Simplilearn 

Applied Generative AI Specialization

What it offers- Gain a comprehensive understanding of applied Generative AI, from mastering foundational concepts such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Prompt Engineering to exploring advanced topics like large language models (LLMs), attention mechanisms, and LLM fine-tuning. This Generative AI course offers a holistic approach that equips you with the skills to develop and refine cutting-edge AI applications. Other tools taught ChatGPT, DALL-E 2, OpenAI, and Hugging Face.

Delivered by Purdue University Online and Simplilearn, and in Collaboration With AWS

Generative AI for business transformation

What it offers- The evolution of Generative AI, especially in models like GPT-4, showcases unprecedented advancements in natural language generation. This Generative AI course offers a holistic understanding of applied Generative AI, including software engineering, data analytics, sales and marketing, customer service operations, and product research. You can learn code generation, debugging, automated documentation, and other skills like data interpretation, predictive modeling, and anomaly detection.

Delivered by Purdue University Online and Simplilearn, and in Collaboration With AWS

AI and Machine Learning Bootcamp

What it offers- Enroll in this course to enhance your skills in Machine Learning, Deep Learning, Reinforcement Learning, NLP, Generative AI, Explainable AI, Computer Vision, Prompt Engineering, ChatGPT, and more. This immersive AI Bootcamp thoroughly explains AI concepts and provides practical experience, equipping you to secure a high-profile job where your knowledge of AI tools and strategic planning will enable you to make highly impactful business decisions.

Offered in Collaboration with Caltech CTME

Post Graduate Program in AI and Machine Learning

What it offers- Master essential skills in ML, Deep Learning, NLP, Computer Vision, Reinforcement Learning, Generative AI, Prompt Engineering, and more with our comprehensive AI and ML course. Designed to propel your career in artificial intelligence and machine learning, each module is meticulously crafted to cover cutting-edge topics. Dive into the latest advancements including ChatGPT, Generative AI, and Explainable AI, and gain expertise that's in high demand across industries.

Delivered in collaboration with Purdue University Online and IBM

Why must you choose Simplilearn for a Generative AI certification?

  1. Extensive curriculum: Simplilearn provides a structured and comprehensive curriculum designed by industry experts, covering all aspects of Generative AI from basics to advanced topics.

  2. Hands-on learning and Capstone projects: The Generative AI courses include hands-on projects that allow you to apply theoretical knowledge to real-world scenarios, enhancing practical skills.

  3. Classes led by industry experts and masterclass by university faculty: You'll learn from experienced instructors who are practitioners in the field of Generative AI, providing insights and guidance based on industry best practices.

  4. Flexibility: Simplilearn offers flexible learning options, including self-paced learning and live online classes, accommodating different schedules and learning preferences.

  5. Industry-recognized certification: Upon completion, you receive a globally recognized certificate from Simplilearn, demonstrating your proficiency in Generative AI to employers and peers.

  6. Career support: Access to career support services such as resume building, interview preparation, and job placement assistance, helping you leverage your certification effectively in the job market.

  7. Community and Networking: Join a community of learners and professionals interested in Generative AI, fostering networking opportunities and continuous learning beyond the course.

Here’s your golden opportunity to earn a certification from top globally recognized universities

There’s no better opportunity than acquiring Generative AI certifications from institutions like Purdue University, IBM, and Simplilearn. A certificate from any of these reputed organizations will validate your proficiency in artificial intelligence and machine learning, this boosting your prospects for upskilling and career growth.

Job roles and opportunities that you can bag after completing any of these Generative AI courses

If you complete any Generative AI certification course from Simplilearn, you will make significant progress towards many high-paying job roles across industries. 

Here are some of the lucrative roles you can check out:

  • Research Scientist: Conduct advanced research and innovate in Generative AI model and algorithm development.

  • AI Product Manager: Lead the development of products and applications powered by Generative AI.

  • Ethical AI Manager: Address ethical implications and biases in AI-generated content.

  • ML Engineer: Deploy Generative AI models for real-world applications.

  • NLP Engineer: Create Generative AI models for tasks such as text generation, machine translation, and text summarization.

  • Data Scientist: Prepare and refine datasets essential for training Generative AI models.

  • Game Developer: Utilize Generative AI to craft game elements like maps and characters.

  • Autonomous Systems Engineer: Enhance autonomous agents with Generative AI to enable more natural behaviors.

Generative AI Courses FAQs

  • 1. What Is Generative AI?

    Generative AI is a branch of artificial intelligence that creates new, unique content by learning from existing data. It can produce text, images, videos, audio, and 3D models. Recent advancements, such as OpenAI's GPT for text generation and Midjourney for image creation, have showcased its potential in transforming various fields, from art and content creation to problem-solving and research.

  • 2. What Is The Difference Between AI And Generative AI?

    Artificial intelligence (AI) is the capability of a machine to perform cognitive functions similar to the human brain, such as learning, reasoning, interaction, and problem-solving. Traditional AI, also known as conventional AI or artificial general intelligence, performs tasks based on preset rules. Common applications of AI technology include search engines, stock trading, and medical diagnosis.

    Generative AI, in contrast, creates new content by using existing data. This can involve generating images, writing text, or creating videos that resemble the data it was trained on.

  • 3. How Does Generative AI Work?

    Generative AI leverages neural networks to identify patterns and structures in data provided by human intelligence. The training process can be supervised, semi-supervised, or unsupervised.

    • Supervised Learning: The model is trained on a labeled dataset, learning by example to make predictions and adjust based on known outcomes.
    • Semi-Supervised Learning: Combines a small amount of labeled data with a larger amount of unlabeled data, using the labeled data to guide the learning process.
    • Unsupervised Learning: The model is trained on an unlabeled dataset, identifying patterns and structures independently, useful for discovering hidden patterns and creating foundational models.

  • 4. What Are The Benefits Of Generative AI?

    Generative AI offers several key benefits:

    • It creates new, original content that resembles human-generated work, which is valuable in various entertainment industries.
    • It enhances existing AI models.
    • It analyzes complex data to make predictions, improving business processes and functions.
    • It automates tasks, saving time and resources.

  • 5. What Are The Different Types of Generative AI Models?

    Generative AI is typically classified into three main types:

    • Transformer Generative AI Models: These neural networks, primarily used for natural language processing (NLP) tasks, process sequential data and identify relationships. They serve as the foundation for most advanced models.
    • Generative Adversarial Networks (GANs): This type of generative AI employs two neural networks to create realistic content, making it particularly useful in art and content creation.
    • Variational Autoencoders (VAEs): This generative AI compresses data into a lower-dimensional space to find patterns. The system then learns to generate new data by sampling from this compressed space.

  • 6. What Is The Role Of Training Data In AI Models?

    Training data is the input provided to generative AI models. This data is analyzed and processed to create neural networks, which then enable the generative AI model to perform its tasks.

  • 7. Why Should One Learn Generative AI?

    Generative AI is rapidly expanding, with projections indicating its usage will grow from 1% to 10% over the next decade. Bloomberg Intelligence estimates the generative AI market could reach $41.3 trillion by 2032, with a compound annual growth rate (CAGR) of 42%. As AI finds applications across various industries, more major companies are adopting it to drive their growth, leading to an increasing demand for generative AI models. Generative AI simplifies and speeds up tasks, making it highly valuable. However, its effectiveness depends on the quality of the tasks and prompts it is given. Therefore, mastering generative AI and developing new tools is essential.

  • 9. Will Generative AI Take Up People's Jobs?

    Generative AI is highly effective in automating tasks and processing complex data beyond human comprehension. However, creating generative AI tools and models still relies on human expertise. Additionally, most generative AI models need human input to assign tasks and provide prompts. As the use of generative AI grows, so will the demand for employees skilled in these tools. Generative AI, therefore, is a chance to create a symbiotic relationship with artificial intelligence, helping improve an employee's work capabilities and efficiency.

  • 10. What Are The Real World Applications Of Generative AI?

    Generative AI is gradually being applied across various fields, including medicine, engineering, and business. Its capabilities, such as speech generation and predictive modeling, are widely utilized in areas such as:

    • Storyline Generation: Creating new characters, storylines, plot twists, and content ideas.
    • Video Games: Designing landscapes, characters, and narratives.
    • Music: Composing new music that aligns with an artist's style.
    • Image Synthesis: Producing realistic images for art, graphics, and design.
    • Text Generation: Generating text for chatbots, language translation, virtual assistants, and media content.
    • Data Augmentation: Creating synthetic data to support the development of other machine learning models.
    • Medicine: Enhancing medical imaging and aiding in drug discovery by generating new molecular structures.
    • Product Design: Exploring and testing different design variations in architecture and engineering.

  • 11. Which Are The Most Popular Generative AI Systems?

    The most popular generative AI tools include:

    • GPT-4: An OpenAI large language model, GPT-4 is a multimodal model that can process both text and images. It can follow natural language directives and interact with external interfaces.
    • ChatGPT: This widely used OpenAI tool excels in content development, understanding natural language, and providing generative AI solutions. It processes text inputs for creative writing, conversation, and answering questions.
    • AlphaCode: A transformer language model-based tool, AlphaCode trains users in multiple programming languages.
    • GitHub Copilot: A collaboration between GitHub and OpenAI, Copilot is a generative AI tool for code completion. It learns from open-source code and supports various programming languages.

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