Master the Machine Muse Build Generative AI with ML
What you'll learn
- Implement practical applications of generative AI in various domains.
- Build and deploy generative AI models using popular frameworks and tools.
- Craft generative models using machine learning techniques
- Train AI to generate creative text formats (like poems!)
- Master the fundamentals of Generative Adversarial Networks (GANs)
- Understand the fundamentals of generative AI and machine learning.
Requirements
- No prior experience with AI or deep learning is required, but it will be helpful.
- A computer with internet access to download necessary software and tools.
- Basic understanding of programming concepts (preferably in Python).
- Curious coders with a basic understanding of Python
- Artists and designers who want to explore AI-powered tools
- Anyone fascinated by the potential of generative AI
Description
Unlock the creative potential of artificial intelligence with "Master the Machine Muse: Build Generative AI with ML." This comprehensive course takes you on an exciting journey into the world of generative AI, blending the art of machine learning with the science of creativity. Whether you're an aspiring data scientist, a tech enthusiast, or a creative professional looking to harness the power of AI, this course will provide you with the skills and knowledge to build and deploy your generative models.
Course Highlights:
- Introduction to Generative AI: Understand the fundamentals of generative AI and its applications across various domains such as art, music, text, and design.
- Foundations of Machine Learning: Learn the core concepts of machine learning, including supervised and unsupervised learning, and how they apply to generative models.
- Deep Learning for Creativity: Dive deep into neural networks and explore architectures like GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformers that are driving the generative AI revolution.
- Hands-On Projects: Engage in practical, hands-on projects that will guide you through the process of building your generative models. From generating art to composing music, you'll experience the thrill of creating with AI.
- Python Programming: Gain proficiency in Python programming, focusing on libraries and frameworks essential for generative AI, such as TensorFlow, PyTorch, and Keras.
- Ethics and Future of Generative AI: Discuss the ethical considerations and future implications of generative AI, ensuring you are well-equipped to navigate this rapidly evolving field responsibly.
Who Should Enroll:
- Data Scientists and Machine Learning Engineers looking to specialize in generative models.
- Artists, Musicians, and Designers interested in exploring AI as a tool for creativity.
- Tech Enthusiasts and Innovators eager to stay ahead in the field of AI.
- Students and Professionals aiming to enhance their skill set with cutting-edge technology.
Prerequisites:
- Basic understanding of Python programming.
- Familiarity with machine learning concepts is beneficial but not required.
Course Outcomes:
By the end of this course, you will:
- Have a strong grasp of generative AI concepts and techniques.
- Be able to build and train generative models using state-of-the-art machine learning frameworks.
- Understand the ethical considerations and potential impacts of generative AI.
- Be prepared to apply generative AI skills in real-world projects and innovative applications.
Join us in "Master the Machine Muse: Build Generative AI with ML" and embark on a creative journey that merges technology with imagination, empowering you to shape the future of AI-driven creativity.
Who this course is for:
- Basic programming experience (Python preferred, but not required)
- Aspiring data scientists, machine learning enthusiasts, software developers, and tech professionals
- Who want to delve into the world of generative AI
- Students and Researchers who wish to explore advanced AI concepts and applications.
Instructor
- 4.0 Instructor Rating
- 1,128 Reviews
- 70,108 Students
- 46 Courses
Hello, I'm Akhil Vydyula — Lead Data Engineer at Publicis Sapient, and Former Senior Data Scientist at PwC.
With over 5 years of rich industry experience and a strong focus on the BFSI sector, I’ve led and delivered end-to-end data and analytics solutions that power strategic decisions and transform business outcomes.
At Publicis Sapient, I currently lead complex data engineering initiatives, leveraging my deep expertise in cloud-native platforms like AWS to architect robust, scalable data pipelines. My work spans across developing and optimizing ETL workflows using PySpark and Spark SQL, orchestrating data flows via EMR, Step Functions, and EventBridge, and driving real-time and batch data processing into PostgreSQL (RDS/Redshift) environments. I've also implemented AWS Glue and DMS to seamlessly replicate and transform large-scale on-premise data into cloud-native formats.
Previously, at PwC, I specialized in advanced analytics and machine learning within the Advisory Consulting practice. I’ve built and deployed predictive models using statistical analysis, regression, classification, clustering, and text mining—particularly for risk identification and decision modeling. My passion lies in transforming raw data into actionable insights through effective data storytelling and visualization.
In parallel to my corporate career, I bring over 5 years of teaching experience, mentoring hundreds of aspiring data professionals. I’m deeply committed to helping students break into the data industry by translating real-world challenges into practical learning experiences.
Whether it's building data pipelines, uncovering business insights, or shaping the next generation of data talent, I thrive at the intersection of technology, strategy, and impact.
Let’s connect if you're passionate about data, eager to learn, or looking to collaborate on meaningful, data-driven initiatives.