TLDR: The University of Melbourne, in collaboration with Emeritus, has unveiled a 9-month part-time ‘Advanced Program in Generative AI and Machine Learning’ tailored for professionals in India. Commencing on December 18, 2025, this blended online and in-person course aims to provide comprehensive, hands-on expertise in designing, deploying, and scaling AI/ML solutions. The curriculum spans data science, Python programming, machine learning, deep learning, and ethical AI, offering optional IBM certifications and robust career support.
Mumbai, India – November 4, 2025 – In a significant move to address the growing demand for Artificial Intelligence (AI) and Machine Learning (ML) expertise, the University of Melbourne has partnered with Emeritus, a global leader in executive education, to introduce the ‘Advanced Program in Generative AI and Machine Learning’. This 9-month, part-time program is specifically designed for professionals in India, aiming to equip them with the advanced skills necessary to navigate and lead in the rapidly evolving AI landscape.
The program is set to commence on December 18, 2025, and will be delivered through a blended learning format. Participants will engage with recorded online lectures, weekly live sessions led by domain experts, faculty masterclasses, and a series of hands-on projects and assignments. A unique aspect of the program includes a 2-day in-person immersion at the University of Melbourne Global Centre in Delhi, providing a valuable opportunity for networking and practical application.
According to industry insights, “Generative AI has rapidly moved from experimentation to enterprise adoption, reshaping industries worldwide.” This sentiment is echoed by data indicating that “36% of Indian enterprises have allocated a dedicated budget for Generative AI in 2025,” and “GenAI is projected to boost India’s IT industry’s productivity by up to 45%.” The program directly responds to this urgent industry need for talent capable of building, deploying, and scaling AI/ML solutions responsibly.
Targeted at a diverse group of professionals, including data scientists, software engineers, business analysts, and product managers, the course is ideal for those looking to transition into AI/ML roles or enhance their current projects with AI capabilities. While not strictly essential, a bachelor’s degree or higher, coupled with foundational knowledge in mathematics and programming, is recommended for optimal learning.
The comprehensive curriculum is structured across multiple pillars, blending foundational concepts with hands-on upskilling. Key topics include:
Fundamentals of Data Science: Covering Python programming and essential statistical methods.
Core AI and ML Implementation: Applying mathematical, statistical, and programming skills to build core AI and ML algorithms, including supervised and unsupervised techniques.
Deep Learning: Hands-on experience with models like CNNs, RNNs, and encoder-decoder transformers for image recognition and natural language understanding.
Natural Language Processing (NLP): Developing NLP models using transformer architectures for tasks such as text generation and translation.
Computer Vision and Speech Recognition: Implementing deep learning-based systems for these critical AI applications.
Generative AI: Mastering concepts like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), advanced Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
Reinforcement Learning: Utilizing reinforcement learning to build intelligent agents for complex decision-making.
Model Deployment and MLOps: Deploying ML models using tools like Flask and Streamlit to create interactive, real-world AI applications.
Ethical AI: Understanding ethical, social, and environmental considerations in AI design and deployment, ensuring responsible innovation.
Participants will gain hands-on experience with a wide array of industry tools and libraries, including TensorFlow, PyTorch, Hugging Face, Kubernetes, Jupyter Notebook, Docker, LLaMA, SQL Server, and various Python libraries like pandas, NumPy, and Scikit-learn.
The program offers optional IBM certifications in ‘Deep Learning with TensorFlow,’ ‘Responsible and Ethical Generative AI,’ and ‘Developing Generative AI Applications using Python,’ providing participants with globally recognized credentials. Upon successful completion, learners will receive a Certificate of Completion from the University of Melbourne, provided they achieve a minimum overall score of 70% on all mandatory assignments and the capstone project, and maintain at least 50% attendance in live sessions.
The esteemed faculty includes Professor Eduard Hovy, Executive Director of Melbourne Connect; Dr. Jey Han Lau, Senior Lecturer in Natural Language Processing; Dr. Mel Mistica, Senior Research Fellow and Data Specialist in Natural Language Processing; and Professor Jeannie Paterson, Professor of Law and Director of the Centre for AI and Digital Ethics.
Beyond technical skills, the program emphasizes career readiness, offering comprehensive career support services. These include a six-month IIMJobs Pro subscription, access to a resume-builder tool, career preparation modules, and guidance on building a professional GitHub portfolio. As stated by the University, “In an increasingly competitive landscape where employers prioritise adaptability and AI fluency, this program helps you build the credibility and depth to lead transformation—across roles, functions and industries.”
Also Read:
- IIT Delhi’s IHFC, Simplilearn, and Microsoft Launch Advanced Professional Programs in AI and Data Analytics
- OpenAI Launches Executive Education Program in Amsterdam to Foster AI Leadership
The program fee is INR 1,80,000 plus GST, with flexible payment options available. The initiative underscores the University of Melbourne’s commitment to broadening access to high-quality education through collaborative and engaging online formats, maintaining its reputation as a leading global institution.
