Artificial Intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or other animals. It is a field of study in computer science that develops and studies intelligent machines. Such machines may be called AIs.
AI technology is widely used throughout industry, government, and science. Some high- profile applications are: advanced web search engines (e.g., Google Search), recommendation systems (used by YouTube, Amazon, and Netflix), understanding human speech (such as Google Assistant, Siri , and Alexa ), self-driving cars (e.g., Waymo ), generative and creative tools ( ChatGPT and AI art), and superhuman play and analysis in strategy games (such as chess and Go)
AI Engineer focuses on developing advanced AI algorithms and neural network architectures. Their duties include collecting data, refining machine learning (ML) models, and integrating AI into applications. Artificial intelligence is transforming the world and helping organizations of all sizes grow, innovate, and make smarter decisions. The Artificial Intelligence Professional Programme will equip you with knowledge of the principles, tools, techniques, and technologies driving this transformation.
Accelerate your career with this comprehensive AI and ML course that delivers a high- engagement learning experience leveraging SBIT academic excellence in the field of AI and ML. SBIT offers B.Tech in CSE and B.Tech in IT Engineering with minor specialization in AI and ML With the following objectives
SBIT offers B.Tech in CSE and B.Tech in IT Engineering with minor specialization in AI and ML With the following objectives
1. Understanding AI Concepts:
Objective 1: Students will acquire a foundational understanding of key AI concepts, including machine learning, neural networks, natural language processing, and computer vision.
2. Problem-Solving with AI:
Objective 2: Students will develop the ability to identify problems that can be addressed using AI techniques and select appropriate methodologies for problem- solving.
3. Programming and Implementation:
Objective 3: Students will gain hands-on experience in implementing AI algorithms, using programming languages such as Python, and utilizing popular AI libraries and frameworks.
4. Machine Learning Fundamentals:
Objective 4: Students will comprehend the fundamental principles of machine learning, including supervised learning, unsupervised learning, and reinforcement learning.
5. Data Preprocessing and Feature Engineering:
Objective 5: Students will learn techniques for data preprocessing, feature engineering, and understanding the importance of high-quality data in AI model development.
6. Evaluation and Model Selection:
Objective 6: Students will understand methods for evaluating AI models, selecting appropriate evaluation metrics, and making informed decisions about model selection based on performance.
7. Ethical Considerations in AI:
Objective 7: Students will be aware of ethical considerations and societal implications related to AI, including issues of bias, fairness, transparency, and accountability.
8. Real-world Applications:
Objective 8: Students will explore real-world applications of AI in various domains, such as healthcare, finance, natural language processing, and computer vision.
9. Collaboration and Teamwork:
Objective 9: Students will develop collaboration and teamwork skills through group projects, fostering an understanding of the interdisciplinary nature of AI.
10. Communication Skills:
Objective 10: Students will enhance their ability to communicate AI concepts and findings effectively, both in written reports and oral presentations.
11. Continuous Learning:
Objective 11: Students will be encouraged to embrace a mindset of continuous learning, staying updated on the latest advancements in AI and related technologies.
12. Critical Thinking:
Objective 12: Students will cultivate critical thinking skills, enabling them to assess and critique AI solutions and research.
These objectives collectively aim to equip students with a solid foundation in AI concepts, technical skills in implementation, ethical considerations, and the ability to apply AI techniques to real-world problems. As AI is a rapidly evolving field, fostering a mindset of continuous learning is crucial for students to adapt to emerging technologies and advancements