Unleash Your Potential: Master AI Engineering

Shape the Future with Cutting-Edge Technology and Innovation

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Why Choose Our AI Engineering Program at HUST University?

Choose HUST University's AI Engineering Program for a world-class education led by expert faculty, hands-on training in cutting-edge AI technologies, and strong industry connections. With state-of-the-art facilities and a supportive community, HUST empowers you to lead the AI revolution and shape the future.

Cutting-edge Curriculum

Learn the latest AI technologies and methodologies from industry experts

Industry-Aligned

Hands-on Projects

Work on real-world AI projects and build your portfolio with practical experience

Project-Based

Expert Mentorship

Get guidance from experienced professionals and industry leaders

Personalized

Global Recognition

Earn a degree recognized worldwide with international accreditation

Accredited

Research Facilities

Access state-of-the-art labs and research facilities for AI development

Advanced

Industry Partnerships

Benefit from our partnerships with leading tech companies worldwide

Connected

International Exposure

Opportunities for global exchange programs and international conferences

Global

Career Support

Comprehensive placement assistance and career development programs

100% Support

Career Opportunities

HUST University's AI Engineering degree opens doors to dynamic careers as machine learning engineers, data scientists, or AI researchers with top tech firms and startups. With soaring global demand, our program equips you for high-impact roles in healthcare, finance, and more, driving innovation and offering competitive salaries.

AI Engineer

Design and implement AI solutions for various industries

₹8-12 LPA

Machine Learning Engineer

Develop and deploy machine learning models

₹10-15 LPA

Data Scientist

Analyze complex data sets and derive insights

₹9-14 LPA

AI Research Scientist

Conduct research in advanced AI technologies

₹12-18 LPA

AI Cloud Architect

Design and implement AI solutions on cloud platforms

₹15-25 LPA

NLP Engineer

Develop natural language processing solutions

₹10-16 LPA

Computer Vision Engineer

Build image and video processing systems

₹11-17 LPA

AI Product Manager

Lead AI product development and strategy

₹14-22 LPA

What Our Students Say

HUST University's AI Engineering students love the program. "Expert mentors and hands-on projects landed me a top AI internship," says Linh. "Innovative labs fueled my machine learning passion," shares Minh. Our students excel, ready to lead in AI.

"The AI Engineering program transformed my career. The hands-on projects and industry exposure were invaluable for my growth."

Student

Rahul Sharma

AI Engineer at Google
Google Placed

"Outstanding curriculum and exceptional faculty. Secured a position at Microsoft immediately after graduation."

Student

Priya Patel

ML Engineer at Microsoft
Microsoft Placed

"The international exposure and research opportunities here are unmatched. Now working on cutting-edge AI projects at Amazon."

Student

Amit Kumar

AI Researcher at Amazon
Amazon Placed

Welcome to the Future of Engineering

Where Innovation Meets Intelligence

What is AI Engineering?

AI Engineering is an interdisciplinary field that combines principles of artificial intelligence, software engineering, and data science to design, develop, and deploy intelligent systems and applications. It focuses on creating scalable, efficient, and ethical AI solutions that solve real-world problems, from predictive analytics to autonomous systems, by leveraging machine learning, deep learning, and advanced algorithms.

Why Choose AI Engineering?

  • Interdisciplinary Skill Development
  • High Demand and Career Growth
  • Future-Proof Profession
  • Impactful Innovation
AI Engineering

100+

Companies Hiring

95%

Placement Rate

₹8L+

Average Package

50+

Industry Partners

Course Curriculum

Year 1: Foundational Skills

Focus: Build a strong foundation in mathematics, programming, and basic sciences.

Semester 1

Calculus I (4 credits)
  • Topics: Limits, derivatives, integrals, applications in optimization
  • Outcomes: Mastery of calculus for AI algorithms
  • Assessment: Assignments (30%), Midterm (30%), Final Exam (40%)
Introduction to Programming (4 credits)
  • Topics: Python basics, variables, loops, functions, data structures
  • Tools: Python, Jupyter Notebook
  • Outcomes: Ability to write and debug Python programs
  • Assessment: Coding Assignments (40%), Labs (30%), Final Exam (30%)
Physics for Engineers (3 credits)
  • Topics: Mechanics, electromagnetism, applications in computing
  • Outcomes: Understanding of physical principles relevant to engineering
  • Assessment: Quizzes (20%), Labs (30%), Final Exam (50%)
Academic Writing and Communication (2 credits)
  • Topics: Technical writing, presentations, teamwork skills
  • Outcomes: Effective communication for engineering projects
  • Assessment: Essays (40%), Presentations (30%), Group Work (30%)

Total Credits: 13

Semester 2

Calculus II (4 credits)
  • Topics: Multivariable calculus, series, differential equations
  • Outcomes: Advanced calculus skills for AI optimization
  • Assessment: Assignments (30%), Midterm (30%), Final Exam (40%)
Object-Oriented Programming (4 credits)
  • Topics: Classes, objects, inheritance, polymorphism, design patterns
  • Tools: Python, PyCharm
  • Outcomes: Ability to design modular, reusable code
  • Assessment: Projects (40%), Labs (30%), Final Exam (30%)
Linear Algebra (3 credits)
  • Topics: Vectors, matrices, eigenvalues, linear transformations
  • Outcomes: Understanding of linear algebra for machine learning
  • Assessment: Assignments (30%), Midterm (30%), Final Exam (40%)
Introduction to Data Analysis (2 credits)
  • Topics: Data visualization, descriptive statistics, basic Excel/Python analysis
  • Tools: Python (pandas, matplotlib), Excel
  • Outcomes: Basic data manipulation and visualization skills
  • Assessment: Labs (50%), Project (30%), Quiz (20%)

Total Credits: 13

Year 1 Total Credits: 26

Year 2: Core Computer Science and Mathematics

Focus: Deepen programming skills, introduce probability, and cover core computer science concepts.

Semester 3

Probability and Statistics (4 credits)
  • Topics: Probability distributions, hypothesis testing, Bayesian inference
  • Outcomes: Statistical foundation for machine learning
  • Assessment: Assignments (30%), Midterm (30%), Final Exam (40%)
Data Structures and Algorithms (4 credits)
  • Topics: Arrays, linked lists, trees, graphs, sorting, searching
  • Tools: Python
  • Outcomes: Efficient algorithm design and implementation
  • Assessment: Coding Assignments (40%), Midterm (30%), Final Exam (30%)
Database Systems (3 credits)
  • Topics: Relational databases, SQL, database design, NoSQL basics
  • Tools: PostgreSQL, MongoDB
  • Outcomes: Ability to design and query databases
  • Assessment: Labs (40%), Project (30%), Final Exam (30%)
Discrete Mathematics (3 credits)
  • Topics: Set theory, logic, combinatorics, graph theory
  • Outcomes: Mathematical reasoning for AI and algorithms
  • Assessment: Assignments (30%), Midterm (30%), Final Exam (40%)

Total Credits: 14

Semester 4

Advanced Statistics for AI (3 credits)
  • Topics: Regression analysis, multivariate statistics, statistical modeling
  • Tools: Python (statsmodels, scipy)
  • Outcomes: Advanced statistical methods for data science
  • Assessment: Assignments (30%), Project (30%), Final Exam (40%)
Operating Systems and Networking (3 credits)
  • Topics: Processes, threads, memory management, TCP/IP, network protocols
  • Outcomes: Understanding of system-level operations for AI deployment
  • Assessment: Labs (40%), Quizzes (20%), Final Exam (40%)
Software Engineering Principles (3 credits)
  • Topics: Software development lifecycle, version control, testing, agile methods
  • Tools: Git, Docker
  • Outcomes: Ability to develop software collaboratively
  • Assessment: Group Project (40%), Assignments (30%), Final Exam (30%)
Introduction to Machine Learning (3 credits)
  • Topics: Supervised learning, linear regression, logistic regression, model evaluation
  • Tools: Python, scikit-learn
  • Outcomes: Basic machine learning model development
  • Assessment: Assignments (30%), Project (30%), Final Exam (40%)

Total Credits: 12

Year 2 Total Credits: 26

Year 3: Core AI and Data Engineering

Focus: Introduce advanced AI concepts, data engineering, and practical applications.

Semester 5

Machine Learning Fundamentals (4 credits)
  • Topics: Classification, clustering, dimensionality reduction, ensemble methods
  • Tools: scikit-learn, NumPy, pandas
  • Outcomes: Ability to build and evaluate machine learning models
  • Assessment: Assignments (30%), Midterm (30%), Final Project (40%)
Data Engineering for AI (3 credits)
  • Topics: ETL pipelines, big data frameworks, data preprocessing, data governance
  • Tools: Apache Spark, Hadoop, PostgreSQL
  • Outcomes: Skills to manage large-scale datasets for AI
  • Assessment: Labs (40%), Group Project (30%), Final Exam (30%)
Ethics and Fairness in AI (2 credits)
  • Topics: Bias in AI, fairness metrics, privacy, AI regulations
  • Outcomes: Understanding of ethical AI practices
  • Assessment: Case Studies (50%), Presentation (30%), Reflection Paper (20%)
Elective 1 (3 credits)
  • Options:
    • Natural Language Processing Basics
    • Computer Vision Fundamentals
  • Tools: NLTK, spaCy, OpenCV, TensorFlow
  • Assessment: Assignments (30%), Project (30%), Final Exam (40%)

Total Credits: 12

Semester 6

Deep Learning Foundations (4 credits)
  • Topics: Neural networks, backpropagation, CNNs, RNNs, optimization
  • Tools: TensorFlow, PyTorch
  • Outcomes: Ability to design and train deep learning models
  • Assessment: Assignments (30%), Midterm (30%), Final Project (40%)
Big Data Analytics (3 credits)
  • Topics: Distributed computing, real-time analytics, data streaming
  • Tools: Apache Kafka, Spark Streaming
  • Outcomes: Skills in analyzing large-scale, real-time data
  • Assessment: Labs (40%), Project (30%), Final Exam (30%)
AI Project Lab (3 credits)
  • Description: Students develop a small-scale AI application
  • Deliverables: Prototype, report, presentation
  • Outcomes: Practical experience in AI development
  • Assessment: Proposal (20%), Implementation (50%), Presentation (30%)
Elective 2 (3 credits)
  • Options:
    • Reinforcement Learning Basics
    • Time Series Analysis
  • Tools: Gym, statsmodels, PyTorch
  • Assessment: Assignments (30%), Project (30%), Final Exam (40%)

Total Credits: 13

Year 3 Total Credits: 25

Year 4: Advanced AI and Industry Readiness

Focus: Master advanced AI techniques, deploy systems, and complete a capstone project.

Semester 7

Advanced Deep Learning (4 credits)
  • Topics: Transformers, transfer learning, GANs, model optimization
  • Tools: PyTorch, TensorFlow, Hugging Face
  • Outcomes: Expertise in state-of-the-art deep learning models
  • Assessment: Assignments (30%), Midterm (30%), Final Project (40%)
AI Systems and Deployment (3 credits)
  • Topics: Model deployment, cloud platforms, containerization, APIs
  • Tools: AWS, Docker, Flask, Kubernetes
  • Outcomes: Ability to deploy scalable AI systems
  • Assessment: Labs (40%), Deployment Project (30%), Final Exam (30%)
AI Project Management (2 credits)
  • Topics: Agile methodologies, AI project lifecycle, risk management
  • Outcomes: Skills to manage AI projects
  • Assessment: Case Studies (40%), Group Simulation (30%), Final Report (30%)
Elective 3 (3 credits)
  • Options:
    • Generative AI Models
    • AI for IoT
  • Tools: PyTorch, TensorFlow Lite
  • Assessment: Assignments (30%), Project (30%), Final Exam (40%)

Total Credits: 12

Semester 8

Capstone AI Project (6 credits)
  • Description: Students develop a comprehensive AI solution for a real-world problem
  • Deliverables: Proposal, report, deployed application, presentation
  • Outcomes: End-to-end AI project experience
  • Assessment: Proposal (10%), Progress Reviews (20%), Final Deliverables (50%), Presentation (20%)
Industry Internship or Research Seminar (3 credits)
  • Options:
    • Internship: Work with a tech company on an AI project
    • Research Seminar: Literature review and presentation on an AI topic
  • Outcomes: Industry exposure or research skills
  • Assessment: Report (50%), Presentation (30%), Supervisor Evaluation (20%)
Elective 4 (3 credits)
  • Options:
    • AI for Robotics
    • Federated Learning
  • Tools: ROS, TensorFlow Federated
  • Assessment: Assignments (30%), Project (30%), Final Exam (40%)

Total Credits: 12

Year 4 Total Credits: 24

Fee Structure

Ist, IIst, IIIrd, IVth Year (Hostel-Single Room)

Particulars RMB USD (Approx) INR (Approx)
TUITION FEES 30,000/Year 4110/Year 350918/Year
HOSTEL FEES 14400/Year 1973/Year 168441/Year
LIVING COST 10,000 (Approx)/Year 1370/Year 116973/Year
HEALTH INSURANCE 800/Year 110/Year 9358/Year
RESIDENTIAL PERMIT 400/Year 55/Year 4679/Year
PHYSICAL EXAMINATION 500 (One Time Only) 69 (One Time Only) 5849 (One Time Only)
TEXT BOOK FEES 200/Year 28/Year 2340/Year
TOTAL 56300/Year 7715/Year 658558/Year

Ist, IIst, IIIrd, IVth Year (Hostel-Double Room)

Particulars RMB USD (Approx) INR (Approx)
TUITION FEES 30,000/Year 4110/Year 350918/Year
HOSTEL FEES 8400/Year 1151/Year 98257/Year
LIVING COST 10,000 (Approx)/Year 1370/Year 116973/Year
HEALTH INSURANCE 800/Year 110/Year 9358/Year
RESIDENTIAL PERMIT 400/Year 55/Year 4679/Year
PHYSICAL EXAMINATION 500 (One Time Only) 69 (One Time Only) 5849 (One Time Only)
TEXT BOOK FEES 200/Year 28/Year 2340/Year
TOTAL 50300/Year 6893/Year 588374/Year

Ready to Shape Your Future in AI?

Join our comprehensive AI Engineering program and become part of the next generation of technology leaders.

Expert Faculty

Learn from industry professionals

Hands-on Projects

Real-world AI applications

Industry Network

Connect with top companies

Apply Now View Curriculum

Benefits of AI Engineering

AI engineering enhances efficiency, enables data-driven decisions, accelerates innovation, and offers scalable personalization. It automates tasks, empowers precise choices, drives transformative technologies, and delivers tailored solutions for better engagement.

Enhanced Efficiency

Automates tasks, saves time and costs.

Data-Driven Decisions

Analyzes data for precise, informed choices.

Innovation Acceleration

Drives advancements in transformative technologies.

Scalable Personalization

Delivers tailored solutions for better engagement.

Future of AI Engineering

HUST University's AI Engineering degree opens doors to dynamic careers as machine learning engineers, data scientists, or AI researchers with top tech firms and startups. With soaring global demand, our program equips you for high-impact roles in healthcare, finance, and more, driving innovation and offering competitive salaries.

Growing Demand

The AI industry is expected to grow at a CAGR of 37.3% from 2023 to 2030

Career Opportunities

Multiple career paths in AI development, research, and implementation

Industry Impact

AI is transforming every industry from healthcare to finance

Attached Programs & Opportunities

HUST University provides diverse programs and opportunities, including innovative courses, research, and industry partnerships. Students gain skills through projects, internships, and global exchanges, preparing them for successful careers.

Industry Partnerships

Collaborate with leading tech companies through our extensive network of industry partners.

  • Paid Internship Programs
  • Industry Mentorship
  • Live Project Experience
  • Career Guidance

Global Exposure

Access international opportunities and build a global network in AI engineering.

  • Student Exchange Programs
  • International Conferences
  • Global Research Projects
  • Cultural Exchange

Professional Certifications

Earn industry-recognized certifications to enhance your career prospects.

  • AWS AI/ML Certification
  • Google TensorFlow
  • Microsoft Azure AI
  • IBM AI Engineering

Salary Structure

AI engineer salaries differ globally. In India, entry-level roles earn ₹8-12 LPA, with seniors at ₹20-50 LPA. Abroad, US entry-level salaries range from $80,000-$120,000, while senior roles fetch $150,000-$300,000+, based on expertise and demand.

Entry Level

₹8-12 LPA

  • AI Engineer
  • Machine Learning Engineer
  • Data Scientist

Mid Level

₹12-20 LPA

  • Senior AI Engineer
  • AI Project Lead
  • Research Scientist

Senior Level

₹20+ LPA

  • AI Architect
  • AI Director
  • Chief AI Officer

In Partnership with HUST University, China

World-Class Education

Learn from top-ranked university in China with strong focus on AI and technology

Global Recognition

Degree recognized worldwide with international accreditation

Research Excellence

Access to cutting-edge research facilities and industry partnerships

International Network

Connect with students and faculty from around the world

State-of-the-art AI laboratories
Industry-standard equipment and tools
Expert faculty with industry experience
International exchange programs
Career placement support
Research publication opportunities
Apply Now Visit HUST Website

Industries Impacted by the AI Revolution

Healthcare

Construction

Manufacturing

Supply Chain Management

Cybersecurity

Business Intelligence

Transportation

Education

Retail

Information Technology

Get in Touch

Have questions about our AI Engineering program? We're here to help you take the next step in your education journey.

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C-109, Sector 2, Noida
Uttar Pradesh, India - 201301

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growellpvt@gmail.com

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Sunday: Closed

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