B.Tech. Computer Science & Engineering(AI & ML)

Welcome to the world of innovation and possibilities with our comprehensive B.Tech program!

Overview

  • Location - GHRISTU Pune
  • Duration -4 years
  • Course Type - Full time
  • Affiliated / Approval - UGC

This program equips you with the fundamental knowledge, practical skills, and problem-solving abilities crucial for success in various engineering disciplines. Through a rigorous curriculum and hands-on learning experiences, you'll gain a solid foundation in core engineering principles while exploring and discovering your specific interests.

Key Areas of Focus

    • Engineering Mathematics: Master calculus, linear algebra, differential equations, and other mathematical tools essential for engineering analysis and problem-solving.
    • Computer Fundamentals: Have a strong foundation in programming languages, data structures, algorithms, and computer architecture, the essential building blocks for understanding working of Computer Systems and security challenges faced
    • Data Structures and Algorithms: Gain a deep understanding of existing data structures and algorithms, their benefits, and challenges
    • Artificial Intelligence: Learn essential about Artificial intelligence, Weak/Narrow AI, Explainable AI, Generative AI, Intelligent Agents, Game Theory
    • Supervised & Unsupervised learning: Learn essentials supervised & unsupervised algorithms to train the models and solve complex problems, classification, regression, clustering, Association.
    • Decision Intelligence: gain deep understanding about Structured data, unstructured data, semi-structured data, Data mining concepts of Data Extraction, transformation, Load Tools of Business Intelligence
    • Programming Fundamentals: Learn essential programming languages like Python or C++, grasp algorithms and data structures, and gain the ability to write basic code for engineering applications.
    • Machine Learning-: Gain deep understanding of different Cluster analysis algorithms like k-mean algorithm, Agglomerative hierarchical clustering, Gaussian mixture model to solving complex problems

Learning Outcomes

  • Graduate with a strong foundation in core engineering principles applicable across various disciplines.
  • Develop critical thinking and problem-solving skills to tackle complex engineering challenges.
  • Hands-on Programming skills through laboratory experiments, workshops, Internships and projects.
  • Gain the necessary skills and knowledge to pursue career in fields of Artificial Intelligence and Machine Learning.
  • Build a foundation for further specialization in various Interdisciplinary engineering fields.
  • Adapt to evolving technologies, tools, and methodologies in the field of Artificial Intelligence and Machine learning to remain competitive and innovative.

Career Opportunities

A Bachelor of Technology (B. Tech) degree in Computer Science & Engineering with a specialization in Artificial Intelligence (AI) and Machine Learning (ML) offers a wide range of exciting career opportunities at the forefront of technology. Here are some common career paths you could pursue:

  • Machine Learning Engineer: Machine learning engineers design, implement, and deploy machine learning models and algorithms to solve real-world problems. They work on tasks such as data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation.
  • Data Scientist: Data scientists analyze large datasets to extract insights and patterns using statistical techniques, machine learning algorithms, and data visualization tools. They work on tasks such as exploratory data analysis, predictive modeling, clustering, classification, and regression.
  • AI Research Scientist: AI research scientists conduct research and development activities to advance the state of the art in artificial intelligence. They explore topics such as deep learning, natural language processing, computer vision, reinforcement learning, and generative adversarial networks.
  • AI Software Developer: AI software developers build AI-powered applications and systems that leverage machine learning and other AI techniques. They work on tasks such as integrating AI algorithms into software applications, developing AI-driven user interfaces, and optimizing AI models for performance and scalability.
  • Computer Vision Engineer: Computer vision engineers develop algorithms and systems for analyzing and interpreting visual data, such as images and videos. They work on tasks such as object detection, image classification, image segmentation, and facial recognition, with applications in fields like autonomous vehicles, surveillance, healthcare, and augmented reality.
  • Natural Language Processing (NLP) Engineer: NLP engineers work on understanding and generating human language using computational techniques. They develop algorithms for tasks such as text classification, sentiment analysis, named entity recognition, machine translation, and question answering.
  • Robotics Engineer: Robotics engineers design and develop robots and robotic systems that can perceive, interact with, and navigate the physical world. They work on tasks such as sensor integration, motion planning, localization and mapping, and control algorithms for autonomous robots.
  • AI Ethics and Governance Specialist: AI ethics and governance specialists focus on ensuring that AI technologies are developed and deployed responsibly and ethically. They work on issues such as bias and fairness in AI algorithms, transparency and accountability in AI systems, privacy concerns, and regulatory compliance.
  • AI Product Manager: AI product managers oversee the development and launch of AI-powered products and services. They work with cross-functional teams to define product requirements, prioritize features, and drive product strategy and roadmap based on market needs and customer feedback.
  • AI Consultant:AI consultants provide advisory services to organizations on AI strategy, implementation, and adoption. They assess the feasibility of AI solutions, identify use cases, develop AI roadmaps, and help clients navigate ethical, regulatory, and business challenges related to AI deployment.

These are just a few examples of career opportunities available to B. Tech graduates in Computer Science & Engineering with a specialization in Artificial Intelligence and Machine Learning. The field of artificial intelligence and machine learning is rapidly evolving, offering diverse career paths and opportunities for innovation and impact. Continuous learning, staying updated with the latest research and technologies, and gaining practical experience through projects and internships will be essential for success in this field.