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Edureka

Welcome to the "Generative AI Foundations" course, a learning journey designed to equip you with a deep understanding of Generative AI, its principles, methodologies, and applications across various domains.

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Welcome to the "Generative AI Foundations" course, a learning journey designed to equip you with a deep understanding of Generative AI, its principles, methodologies, and applications across various domains.

By the end of this course, you will have acquired the knowledge and skills to:

- Grasp the foundational concepts and technical intricacies of Generative AI, including its advantages and limitations.

- Apply Generative AI for code generation, enhancing your programming efficiency and creativity in Python and other languages.

- Master the art of prompt engineering to optimize interactions with AI models like ChatGPT, leading to improved outcomes in code generation and beyond.

- Utilize ChatGPT for learning and mastering Python, data science, and software development practices, thereby broadening your technical skill set.

- Explore the revolutionary fields of Autoencoders and Generative Adversarial Networks (GANs), understanding their architecture, operation, and applications.

- Dive into the world of language models and transformer-based generative models, gaining insights into their mechanisms, applications, and impact on the future of AI.

This course is meticulously crafted to cater to a broad audience, including software developers, data scientists, AI enthusiasts, and professionals seeking to leverage Generative AI technologies for innovative solutions.

While prior knowledge of Generative AI Fundamentals or Python Coding is helpful, but it is not a prerequisite to complete the course.

Whether you're looking to enhance your existing skills or embark on a new career path in the field of AI, this course will provide you with the knowledge, practical skills, and confidence to succeed. Join us on this exciting journey into the world of Generative AI!

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What's inside

Syllabus

Gen AI Foundations
This module is designed to equip learners with a solid understanding of Generative AI principles, models, and applications, setting the stage for more advanced exploration. Through engaging lessons that include videos on the overview of Generative AI, its principles, understanding its models, and the advantages and disadvantages, along with practical applications like code generation and prompt engineering, participants will gain valuable insights. This module also emphasizes ethical considerations and includes practice assignments and discussion prompts to encourage active learning and application of concepts. Whether you're new to AI or looking to enhance your understanding of Generative AI's capabilities, this module provides the essential knowledge base to start your journey.
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Autoencoders and GANs
This module is crafted to provide an in-depth understanding of how these models function, their architectural nuances, and their wide array of applications in the tech industry. Starting with the basics of Autoencoders, learners will explore the workings and variations of these networks, including Variational Autoencoders (VAEs), and understand their significance in data compression and generative tasks. The journey continues with an exploration of GANs, from their foundational architecture to the nuances of training and the exploration of their diverse variants. Through practical assignments, engaging video content, and focused readings, participants will gain hands-on experience working with these models, culminating in a deeper comprehension of their capabilities and limitations.
Language Models and Transformer-based Generative Models
This module provides an in-depth exploration of Language Models and Transformer-based Generative Models, foundational elements in natural language processing and artificial intelligence. Starting with an overview of language models, it progresses to cover the revolutionary transformer architecture, detailing its attention mechanism and various advanced models. The module then shifts focus to groundbreaking models such as GPT and BERT, examining their development, capabilities, and the wide array of applications they enable in the AI domain. Concluding with comprehensive assessments, including practice and graded assignments on cutting-edge topics like VAEs and GANs, the module offers a holistic understanding of how these technologies drive innovation in AI research and applications.
Course Wrap-up and Assessment
This final module is designed to consolidate the knowledge and skills learners have acquired throughout the course. It starts with a Practice Project, encouraging learners to apply their understanding in a hands-on manner, thus bridging the gap between theoretical knowledge and practical application. Following this, the module offers a Graded Assignment on Gen AI Fundamentals, aimed at rigorously evaluating the learners' grasp of the key concepts, techniques, and applications explored in the course.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores Generative AI principles, which is essential in software development
Offers hands-on practice through assignments and projects, building practical skills
Covers a broad range of Generative AI applications, enhancing versatility
Taught by Edureka, recognized for delivering quality online courses
Provides a strong foundation for beginners and intermediate learners

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Generative AI Foundations with these activities:
Python coding basics
Refresh your Python coding skills to prepare for the course, ensuring a solid foundation for understanding Generative AI concepts.
Browse courses on Python Basics
Show steps
  • Review basic syntax and data types
  • Practice writing simple Python programs
Seek mentorship from AI experts
Connect with experienced AI professionals to gain personalized guidance, insights, and support throughout your Generative AI learning journey.
Show steps
  • Identify potential mentors through online platforms, industry events, or personal connections
  • Reach out to them, expressing your interest in Generative AI and seeking their mentorship
Code generation with Generative AI
Engage in practice drills to enhance your skills in code generation using Generative AI, improving your efficiency and creativity.
Browse courses on Code Generation
Show steps
  • Set up a development environment and familiarize yourself with Generative AI code generation tools
  • Practice generating code in different programming languages using Generative AI
  • Refine your prompts and techniques to improve the quality and accuracy of the generated code
Two other activities
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Show all five activities
Generative AI project
Embark on a practical project to apply your Generative AI knowledge, solidifying your understanding through hands-on experience.
Browse courses on AI Programming
Show steps
  • Identify a problem or opportunity where Generative AI can be applied
  • Design and implement a Generative AI solution
  • Evaluate the performance and impact of your solution
Blog post on Generative AI applications
Create a blog post showcasing your knowledge of Generative AI applications, reinforcing your understanding and sharing insights with others.
Show steps
  • Research and identify real-world examples of Generative AI applications
  • Analyze and evaluate the impact and benefits of these applications
  • Write a well-structured blog post summarizing your findings

Career center

Learners who complete Generative AI Foundations will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers utilize their knowledge of Generative AI to create ML models that generate high-quality data while preserving privacy and addressing bias. Generative AI ensures the creation of realistic synthetic data, which allows for better model training and reduces the need for human annotation. This course provides a comprehensive overview of Generative AI techniques and their applications, providing you with the necessary skills to excel in this role.
Data Scientist
Generative AI plays a crucial role in the field of Data Science. Data Scientists leverage Generative AI to generate realistic datasets, enhance data quality, and improve model performance. This course delves into the foundational concepts of Generative AI and provides hands-on experience with its applications. By taking this course, you'll gain the knowledge and skills required to become an effective Data Scientist and drive innovation in this rapidly evolving field.
Software Engineer
Generative AI has revolutionized the software development process. Software Engineers utilize Generative AI to automate tasks, improve code quality, and enhance productivity. This course will provide you with a deep understanding of Generative AI techniques, including code generation and prompt engineering. Whether you're looking to enhance your existing skills or transition into the field of AI, this course will equip you with the knowledge and expertise to excel as a Software Engineer.
Natural Language Processing Engineer
Natural Language Processing Engineers leverage Generative AI to create innovative NLP models and applications. Generative AI enables the generation of realistic text, translation, and summarization, enhancing the capabilities ofNLP systems. This course provides a thorough understanding of Generative AI techniques and their applications in NLP, equipping you with the skills necessary to succeed in this dynamic field.
Computer Vision Engineer
Generative AI has opened new possibilities for Computer Vision Engineers. Generative AI techniques enable the generation of synthetic images and videos, improving model training and enhancing the accuracy of computer vision systems. This course delves into the foundational concepts of Generative AI and its applications in computer vision, providing you with the knowledge and skills to drive innovation in this rapidly growing field.
Artificial Intelligence Researcher
Generative AI is a key area of research in Artificial Intelligence. AI Researchers are exploring Generative AI to develop new algorithms, models, and techniques. This course provides a comprehensive overview of Generative AI, equipping you with the theoretical foundation and practical skills to contribute to the advancement of AI research.
Data Analyst
Generative AI is increasingly used by Data Analysts to enhance data quality, generate synthetic data, and identify patterns and insights. This course provides a solid understanding of Generative AI techniques and their applications in data analysis, enabling you to leverage AI to uncover valuable insights and drive decision-making.
Machine Learning Scientist
Machine Learning Scientists leverage Generative AI to create more robust and accurate ML models. Generative AI enables the generation of synthetic data, improving model training and reducing the need for human annotation. This course provides a deep dive into Generative AI techniques and their applications in ML, empowering you to develop innovative ML solutions.
Product Manager
Product Managers are responsible for developing and launching successful AI products. Generative AI is increasingly used to create personalized experiences, generate marketing content, and enhance user engagement. This course provides a comprehensive overview of Generative AI and its applications in product development, equipping you with the knowledge and skills to drive innovation and create successful AI products.
Business Analyst
Business Analysts use Generative AI to identify trends, predict customer behavior, and optimize business processes. Generative AI enables the generation of synthetic data, which allows for better analysis and decision-making. This course provides a solid understanding of Generative AI techniques and their applications in business analysis, empowering you to drive data-driven decisions and improve business outcomes.
UX Designer
UX Designers leverage Generative AI to create innovative and user-friendly interfaces. Generative AI enables the generation of prototypes, mockups, and design concepts, enhancing the design process and improving user experience. This course provides a comprehensive overview of Generative AI and its applications in UX design, equipping you with the skills to create engaging and intuitive user interfaces.
Marketing Manager
Marketing Managers use Generative AI to create personalized marketing campaigns, generate content, and optimize customer engagement. Generative AI enables the creation of unique and relevant marketing materials, improving campaign performance and increasing conversion rates. This course provides a solid understanding of Generative AI techniques and their applications in marketing, empowering you to drive innovation and achieve marketing success.
Sales Manager
Sales Managers leverage Generative AI to identify leads, generate proposals, and close deals. Generative AI enables the creation of personalized sales content, improving lead conversion and increasing sales revenue. This course provides a comprehensive overview of Generative AI and its applications in sales management, equipping you with the skills to drive sales growth and achieve business objectives.
Operations Manager
Operations Managers use Generative AI to optimize processes, improve efficiency, and reduce costs. Generative AI enables the generation of synthetic data, which allows for better analysis and decision-making. This course provides a solid understanding of Generative AI techniques and their applications in operations management, empowering you to drive operational excellence and improve business performance.
Project Manager
Project Managers may find this course helpful in understanding the potential applications of Generative AI in project management. Generative AI can be used to generate project plans, identify risks, and optimize resource allocation. This course provides a comprehensive overview of Generative AI and its applications in project management, equipping you with the skills to drive project success and achieve business objectives.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Generative AI Foundations.
Provides a comprehensive overview of speech and language processing, from its basic principles to advanced techniques. It valuable resource for those who want to learn more about NLP and its applications to speech and language processing.
Provides a comprehensive overview of computer vision, from its basic principles to advanced techniques. It valuable resource for those who want to learn more about computer vision and its applications.
Provides a comprehensive overview of pattern recognition and machine learning, from its basic principles to advanced techniques. It valuable resource for those who want to learn more about pattern recognition and machine learning and its applications.
Provides a comprehensive overview of generative AI, from its basic principles to advanced techniques. It valuable resource for those who want to learn more about generative AI and its applications.
Provides a comprehensive overview of statistical learning, from its basic principles to advanced techniques. It valuable resource for those who want to learn more about statistical learning and its applications.
Provides a comprehensive overview of generative adversarial networks (GANs). It covers the core concepts, techniques, and applications of GANs, and valuable resource for those who want to learn more about this cutting-edge topic.
Provides a comprehensive overview of deep learning, from its basic principles to advanced techniques. It valuable resource for those who want to learn more about deep learning and its applications.
Provides a hands-on introduction to deep learning using the Fastai and PyTorch libraries. It valuable resource for those who want to apply deep learning techniques to real-world problems.
Provides a practical introduction to machine learning, using the Python programming language. It valuable resource for those who want to learn more about machine learning and its applications.
Provides a comprehensive overview of natural language processing, using the Python programming language. It valuable resource for those who want to learn more about NLP and its applications.
Provides a comprehensive overview of the field of deep learning using the Python programming language. It valuable resource for anyone looking to learn how to build and train deep learning models for a variety of tasks.
Provides a comprehensive overview of the field of deep generative models. It valuable resource for anyone looking to learn how to build and train deep generative models for a variety of tasks.

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