B TECH (AI & DS)

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B TECH (AI & DS)

A Bachelor of Technology (B.Tech) in Artificial Intelligence and Data Science (AI & DS) is a four-year undergraduate program designed to provide a solid foundation in AI and data analytics. Below is a concise overview of the core courses typically included in this program, along with their benefits.

Core Courses and Benefits

  1. Introduction to Programming

    • Description: Basics of programming languages and problem-solving techniques, often using Python.
    • Benefits: Develops fundamental coding skills and logical thinking essential for AI and data science.

  2. Data Structures and Algorithms

    • Description: Study of data organization, management, and algorithms for efficient data manipulation.
    • Benefits: Enhances problem-solving skills and the ability to handle large data sets efficiently.

  3. Database Management Systems (DBMS)

    • Description: Principles of database design, SQL, NoSQL databases, and data retrieval techniques.
    • Benefits: Equips students with the skills to manage and query large databases effectively.

  4. Probability and Statistics

    • Description: Fundamentals of probability theory, statistical methods, and data analysis.
    • Benefits: Provides the mathematical foundation necessary for data interpretation and machine learning algorithms.

  5. Machine Learning

    • Description: Concepts of supervised, unsupervised, and reinforcement learning, including algorithm implementation.
    • Benefits: Prepares students to develop and apply machine learning models to real-world problems.

  6. Artificial Intelligence

    • Description: Study of AI principles, including natural language processing, computer vision, and robotics.
    • Benefits: Provides a comprehensive understanding of AI techniques and applications.

  7. Big Data Analytics

    • Description: Techniques for processing and analyzing large-scale data using tools like Hadoop and Spark.
    • Benefits: Equips students with the skills to manage and derive insights from massive data sets.

  8. Data Visualization

    • Description: Methods and tools for visualizing data to communicate insights effectively.
    • Benefits: Enhances the ability to present data findings clearly and compellingly.

  9. Deep Learning

    • Description: Study of neural networks, convolutional networks, and advanced deep learning techniques.
    • Benefits: Prepares students for cutting-edge research and applications in AI.

  10. Data Mining

    • Description: Techniques for discovering patterns and knowledge from large data sets.
    • Benefits: Equips students with skills to extract valuable information from complex data.

  11. Natural Language Processing (NLP)

    • Description: Study of computational techniques for processing and understanding human language.
    • Benefits: Prepares students for applications in text analysis, translation, and conversational AI.

Course Benefits

  1. Strong Technical Foundation: Comprehensive understanding of AI and data science principles.
  2. Analytical Skills: Enhances ability to analyze and interpret complex data.
  3. Career Opportunities: Broad job prospects in data science, AI development, machine learning engineering, and more.
  4. Hands-On Experience: Practical experience through labs, projects, and internships.
  5. Innovation and Research: Encourages creativity and advanced study in AI and data science.
  6. Versatility: Diverse electives allow specialization in areas of interest.

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