Carrier Objective: Learn by myself & teach students, Want to work for the welfare of students.

Research Interest:  Machine Learning

                                                                          Deep Learning

                                                                          Computer Vision

                                                                           Natural Languages Processing

                                                                           Data Science

                                                                            Artificial Intelligence 

Conducted Courses

Objective of this Course:  

The objectives of an artificial intelligence (AI) course within an academic structure typically include the following:

Knowledge and Understanding:** To provide students with a comprehensive understanding of the fundamental concepts, theories, and principles of artificial intelligence, including machine learning, natural language processing, robotics, and computer vision.

Technical Skills:** To equip students with the technical skills required to develop AI applications, including programming in languages such as Python and using AI frameworks and libraries.

Problem-Solving:** To foster the ability to apply AI techniques to solve real-world problems, developing critical thinking and problem-solving skills.

Ethical Considerations:** To educate students about the ethical implications of AI, including issues related to bias, fairness, transparency, and accountability in AI systems.

Research and Innovation:** To inspire and prepare students to engage in AI research and innovation, encouraging them to push the boundaries of AI technology and contribute to the field.

Practical Application:** To enable students to apply AI to various domains such as healthcare, finance, autonomous systems, and more, demonstrating the practical applications of AI.

Data Handling and Analysis:** To teach data acquisition, cleaning, analysis, and interpretation, which are critical skills in AI and machine learning.

Algorithm Development:** To help students develop and understand the algorithms that power AI systems, covering topics like neural networks, deep learning, and reinforcement learning.

Machine Learning:** To provide a deep understanding of machine learning, including supervised learning, unsupervised learning, and reinforcement learning techniques.

Natural Language Processing:** To introduce students to the principles of natural language processing, enabling them to work with text and language data effectively. Computer Vision:** To teach the basics of computer vision, enabling students to work with image and video data and develop applications like object detection and image classification.

Hands-on Experience:** To offer practical experience through projects, lab work, and coding assignments, allowing students to apply AI concepts in real-world scenarios.

Objective  of this Course: A course in data and telecommunications typically aims to provide students with a comprehensive understanding of data transmission, networking, and telecommunications technologies. The specific objectives of such a course may include:

Fundamental Knowledge:** To provide students with a solid foundation in the basic concepts of data communication, networking, and telecommunications.

Networking Principles:** To teach students about networking models, protocols, and the architecture of computer networks, including the OSI model and TCP/IP.

Network Technologies:** To introduce students to various networking technologies, such as Ethernet, Wi-Fi, cellular networks, and the Internet, and their operation.

Data Transmission:** To explain the principles of data transmission, including concepts like modulation, multiplexing, and error detection and correction.

Telecommunications Systems:** To cover various telecommunications systems and technologies, including voice and data transmission over wired and wireless networks.

Network Security:** To educate students on network security concepts and techniques, including encryption, firewalls, intrusion detection systems, and best practices for securing data.

Data Management:** To introduce the basics of data storage, retrieval, and management, including concepts like databases and data centers.

Wireless Communication:** To explore wireless communication technologies, such as cellular networks, Wi-Fi, Bluetooth, and their protocols.

Internet Technologies:** To cover web technologies, including HTML, HTTP, DNS, and web servers, as well as cloud computing and its impact on data and telecommunications.

Protocols and Standards:** To familiarize students with key networking protocols and standards, such as TCP/IP, Ethernet, and Wi-Fi standards.

Network Design:** To teach principles of network design and architecture, including network topology, scalability, and redundancy.

Telecommunication Regulation:** To provide an understanding of the regulatory and legal aspects of telecommunications, including spectrum management and privacy regulations.

Emerging Technologies:** To keep students updated on emerging trends and technologies in data and telecommunications, such as 5G, IoT, and blockchain.

Practical Skills:** To develop practical skills in setting up and configuring networks, troubleshooting network issues, and working with networking equipment.

Problem-Solving:** To foster problem-solving and critical thinking skills in diagnosing and resolving network and data communication problems.

Communication Skills:** To enhance students' ability to communicate effectively within the context of data and telecommunications, including the use of technical documentation and reports.