Artificial Intelligence - Nasscom Futureskills prime
Description
A comprehensive learning pathway that equips learners with foundational to advanced knowledge and skills in Artificial Intelligence, covering theoretical concepts, practical applications, and ethical considerations.
Learning Objectives
Upon completion of this pathway, learners will be able to understand core AI principles and concepts, implement machine learning algorithms and deep learning models, develop AI applications across various domains, apply ethical AI practices and responsible development principles, work with AI frameworks and tools, and design and deploy AI systems in real-world scenarios while maintaining human-centered approaches.
Courses in this Bundle (12)
Data Science and Analytics for AI
Comprehensive data science skills including data collection, cleaning, analysis, visualization, and statistical modeling essential for AI applications...
Deep Learning and Neural Networks
Advanced neural network architectures, deep learning techniques, and frameworks for complex pattern recognition and AI applications.
Programming Fundamentals for AI
Core programming skills in Python, R, and essential software engineering practices required for AI development and implementation.
Natural Language Processing and Text Analytics
Comprehensive study of NLP techniques, language models, and text processing for understanding and generating human language.
Computer Vision and Image Processing
Advanced techniques for visual perception, image analysis, and computer vision applications using traditional and deep learning approaches.
Machine Learning Algorithms and Techniques
Comprehensive study of supervised, unsupervised, and reinforcement learning algorithms with practical implementation and evaluation techniques.
AI Ethics and Responsible AI Development
Comprehensive study of ethical considerations, bias mitigation, fairness, transparency, and responsible practices in AI development and deployment.
Mathematical and Statistical Foundations for AI
Essential mathematical concepts including linear algebra, calculus, probability, and statistics that form the backbone of AI algorithms and models.
AI Development Tools and Frameworks
Hands-on experience with industry-standard AI development tools, frameworks, and platforms for building, deploying, and managing AI applications.
AI Applications and Industry Use Cases
Practical application of AI technologies across various industries including healthcare, finance, retail, manufacturing, and emerging domains with rea...
Robotics and Autonomous Systems
Integration of AI with robotics including motion planning, control systems, sensor integration, and autonomous decision-making for robotic application...
Foundations of Artificial Intelligence
Core concepts, history, and theoretical foundations of artificial intelligence including problem-solving, search algorithms, and knowledge representat...