Post Graduate Diploma in AI and ML
Course Description:
The Post Graduate Diploma in Artificial Intelligence and Machine Learning (PGD in AI & ML) at ISTM is a cutting-edge program designed to provide in-depth knowledge and practical skills in AI technologies. This program covers key topics such as machine learning algorithms, deep learning, natural language processing, computer vision, and AI ethics. Students learn to build AI models, develop intelligent applications, and apply machine learning techniques to solve complex real-world problems. The PGD in AI & ML prepares graduates to be at the forefront of the AI revolution, with a strong focus on hands-on learning and industry-relevant projects.
At ISTM, the PGD in AI & ML program blends theoretical understanding with practical application, enabling students to work with large datasets, create predictive models, and deploy AI solutions in a variety of industries, including healthcare, finance, retail, and autonomous systems. The program is designed for individuals who want to advance their careers in AI and machine learning, equipping them with the tools to innovate in a rapidly evolving technological landscape.
Educational Goals:
- Machine Learning Algorithms: Gain expertise in the development and application of machine learning algorithms to solve data-driven problems.
- Deep Learning and Neural Networks: Understand the architecture and functioning of neural networks and apply them to complex data tasks such as image recognition and speech processing.
- Natural Language Processing (NLP): Learn to process and analyze human language data to develop NLP applications like chatbots and language translation systems.
- AI Model Deployment: Acquire skills in deploying AI models to production environments, ensuring scalability and real-world applicability.
- AI Ethics and Governance: Understand the ethical considerations and implications of AI systems, ensuring responsible use of AI technologies.
- Data Processing and Analytics: Learn to process, clean, and analyze large datasets to train accurate and efficient machine learning models.
Professional Paths:
- AI Engineer: Design and develop intelligent systems and AI models for applications in automation, data analysis, and decision-making.
- Machine Learning Engineer: Build and optimize machine learning models that can predict outcomes, automate tasks, and improve processes.
- Data Scientist: Analyze and interpret complex data to create actionable insights and predictive models for business decision-making.
- NLP Specialist: Develop applications that use natural language processing techniques, such as voice assistants and language translation tools.
- AI Researcher: Conduct advanced research in AI and machine learning to develop new algorithms and innovative AI solutions.
- AI Solutions Architect: Design AI-driven architectures and deploy machine learning models into production for businesses seeking digital transformation.
- Introduction to AI and ML
- Python Programming
- Mathematics for Machine Learning
- Machine Learning Algorithms
- Deep Learning
- Natural Language Processing