Generative AI Course Overview

Generative AI Course Overview

Generative AI certification is an acknowledgment of mastering algorithms that can generate complex, data-like content ranging from text, to images, to music. The certification asserts expertise in using AI to create, enhance or modify content. Industries use Generative AI for tasks such as content automation, virtual assistance, graphic design and other creative work. The basis of Generative AI involves deep learning techniques like Generative Adversarial Networks (GANs), which include two sub-models, a generator to create new outputs, and a discriminator to compare these outputs to the original data. The certification indicates proficiency in these concepts and bolsters the holder's ability to create innovative AI solutions.

NOTE: Please be aware that generative AI vendors, including OpenAI, GPT-3, and Azure Open AI Service, may change their rules, policies, and resources over time. In the context of this course, it is essential to understand that API keys and other resources related to generative AI may be provided to you as per the policies and guidelines set by these vendors.

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  • Live Online Training (Duration : 40 Hours)
  • Per Participant

♱ Excluding VAT/GST

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You can request classroom training in any city on any date by Requesting More Information

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  • Power Packed 18 Hours (Edited from 40 hours of Live Training) Recorded on 02-Jun-24
  • 6 Months Access to Videos
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  • Certificate of Completion
  • Official Coursebook
  • Hands-on labs




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Course Prerequisites

• Basic understanding of Machine Learning concepts
• Knowledge of Deep Learning fundaments
• Proficiency in Python
• Familiarity with Tensorflow and PyTorch frameworks
• Basic data manipulation skills
• Understanding of Neural Networks
• Mathematical skills, particularly in Linear Algebra and Calculus.

Generative AI Certification Training Overview

Generative AI certification training provides detailed insights into the world of artificial intelligence, teaching students to develop algorithms capable of generating data similar to a given set. The course covers key topics such as generative models, deep learning, and neural networks. Students learn about different types of generative models including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. The training also familiarizes students with programming languages like Python, TensorFlow, and PyTorch to handle AI-related tasks.

Why Should You Learn Generative AI?

Learning Generative AI in stats offers numerous benefits, including understanding complex statistical models, developing sophisticated AI systems, enhancing skills in machine learning and data analytics, and gaining proficiency in advanced computational statistics. It equips individuals for future advancements in AI, opening up numerous career opportunities.

Target Audience for Generative AI Certification Training

• AI enthusiasts and technologists interested in learning cutting-edge technology
• Software developers and engineers seeking for upskill
• Data scientists aiming to broaden their AI expertise
• Students studying computer science or relevant disciplines
• Companies or businesses looking to incorporate AI in their operations

Why Choose Koenig for Generative AI Certification Training?

- Certified instructors with comprehensive expertise in Generative AI ensuring quality training
- Significant boost in your career prospects with AI certification from a renowned institute
- Customized training programs tailored to match your learning pace and needs
- Destination training option for immersive learning experience
- Affordable pricing models, driving value for investment
- Credibility of learning from a top training institute with a track record of success
- Flexibility in scheduling with options to choose convenient dates
- Highly interactive, instructor-led online training for global accessibility
- Wide range of course offerings including basic to advanced levels
- Accreditation of the training program ensuring it meets industry standards.

Generative AI Skills Measured

After completing a Generative AI certification training, an individual can acquire skills such as understanding and implementing various generative models, working with tools like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), etc. They can also gain knowledge in deep learning, neural networks and Python programming. Additionally, they can learn to create cutting-edge AI applications like image stylization, music generation, text-to-image synthesis, and can handle real-world challenges by leveraging the power of generative AI models.

Top Companies Hiring Generative AI Certified Professionals

Top tech firms like Google, Microsoft, Amazon, IBM, and Facebook are actively hiring Generative AI certified professionals. These professionals are sought after in various sectors including entertainment, e-commerce, and healthcare industries. Startups and research institutions also show keen interest in such talents.

Learning Objectives - What you will Learn in this Generative AI Course?

The primary learning objectives of a Generative AI course would include understanding the basic theoretical concepts of Generative AI models such as Generative Adversarial Networks (GANs) and Varitational Autoencoders (VAEs). The students would also learn how to implement and train these models using popular AI platforms and languages, such as TensorFlow and Python. Moreover, they would gain insights into the applications and limitations of Generative AI in various fields. Lastly, the course would aim to foster critical thinking around ethical implications and challenges of AI applications in creating synthetic data.