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AI and Machine Learning
Considering AI and Machine Learning? Compare the curriculum, entry requirements, schedule, total cost and provider support before making your next move.
LevelGen AI/Agentic AI ModeOnline DurationUpto 12 Months
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Course Overview
AI and Machine LearningCourse Overview
Eligibility3-8 Months
Step into the future of technology with Artificial Intelligence (AI) and Machine Learning (ML), two of the fastest-growing fields transforming businesses, industries, and everyday life. From intelligent chatbots and self-driving cars to predictive analytics, healthcare innovations, and automated business solutions, AI and ML are shaping the next generation of digital experiences.
Our AI and Machine Learning program is designed to help aspiring learners understand how intelligent technologies work, how machines learn from data, and how AI-powered solutions are developed to solve real-world challenges.
Through a career-oriented curriculum, practical learning activities, industry-relevant tools, and project-based learning, students can develop the technical knowledge and analytical skills required to explore exciting opportunities in the technology sector.
Whether you are a beginner looking to enter the world of technology, a graduate planning a career upgrade, or a working professional interested in emerging technologies, this program can help you move towards a future-ready career.
Start Learning Today – Turn Your Interest in Technology into an Exciting Career in AI and Machine Learning!
Skills
Develop the Skills That Shape Tomorrow's Technology
Build a powerful combination of technical, analytical, and problem-solving skills to understand and create intelligent digital solutions. By studying AI and Machine Learning, learners can develop:
- Programming Skills: Learn Python programming, coding fundamentals, and software development techniques.
- Machine Learning: Understand supervised, unsupervised, and reinforcement learning algorithms.
- Deep Learning: Explore neural networks and advanced learning models.
- Data Analysis: Learn to collect, process, interpret, and analyse complex datasets.
- Artificial Intelligence: Understand intelligent systems, automation, and decision-making technologies.
- Natural Language Processing: Explore how computers understand and process human language.
- Computer Vision: Learn image recognition, object detection, and visual data processing.
- Statistical Knowledge: Develop an understanding of probability, statistics, and mathematical modelling.
- Data Visualisation: Present complex information through meaningful charts, graphs, and dashboards.
- Problem-Solving: Apply computational thinking to solve practical business and technical challenges.
- AI Tools and Frameworks: Gain familiarity with Python libraries, TensorFlow, PyTorch, Scikit-learn, and other relevant technologies.
- Critical Thinking: Evaluate AI models, interpret results, and make data-driven decisions.
Give Your Career a Competitive Edge with Skills Designed for the Intelligent Digital Era!
Who can apply?
Find Your Entry into the World of AI
Artificial Intelligence and Machine Learning offer learning opportunities for students, graduates, aspiring developers, and professionals interested in emerging technologies. This program may be suitable for:
- 12th Pass Students: Students interested in building a future in computing, programming, and intelligent technologies, subject to the programme's eligibility requirements.
- Graduates: Students from relevant academic backgrounds who want to strengthen their knowledge of AI, ML, and data-driven technologies.
- Engineering Students: Learners interested in exploring intelligent automation, algorithms, and advanced computing.
- IT Professionals: Working professionals looking to upgrade their technical knowledge and explore AI-related career opportunities.
- Software Developers: Developers who want to integrate machine learning and intelligent features into applications.
- Data Enthusiasts: Individuals interested in analysing information, discovering patterns, and developing predictive solutions.
- Career Changers: Professionals planning to transition towards technology-driven career opportunities.
- Entrepreneurs: Individuals who want to understand how AI can improve business processes and innovation.
Eligibility: The minimum educational qualification depends on the specific degree, diploma, or certification offered by the institution. Check the official admission requirements before applying.
Job Roles
Explore Exciting Career Opportunities in AI and ML
Artificial Intelligence and Machine Learning are creating new opportunities across IT, healthcare, finance, e-commerce, education, manufacturing, and other industries.
After acquiring relevant qualifications and practical skills, learners may explore career paths such as:
| Job Role | Key Responsibilities |
|---|---|
| 1. AI Engineer | Develop and implement intelligent systems that automate tasks and solve complex problems. |
| 2. Machine Learning Engineer | Design, train, test, and optimise machine learning models. |
| 3. Data Scientist | Analyse large datasets and generate valuable business insights. |
| 4. Data Analyst | Interpret data, prepare reports, and support informed decision-making. |
| 5. AI Research Assistant | Support research activities involving intelligent algorithms and emerging AI technologies. |
| 6. Deep Learning Engineer | Develop neural-network-based applications and advanced learning models. |
| 7. NLP Engineer | Work on language-processing applications, chatbots, and conversational AI. |
| 8. Computer Vision Engineer | Develop applications involving image processing, facial recognition, and object detection. |
| 9. Business Intelligence Analyst | Transform business data into actionable insights. |
| 10. AI Application Developer | Build intelligent software applications using AI-powered technologies. |
| 11. Automation Engineer | Develop technology-based solutions to streamline repetitive business processes. |
| 12. Robotics Software Developer | Work on intelligent software systems used in robotics and automation. |
Your Learning Today Can Become the Foundation of Tomorrow's Technology Career!
Syllabus/Curriculum
Learn the Technologies Behind Intelligent Systems
Explore a comprehensive, career-focused curriculum that introduces learners to essential programming concepts, mathematical foundations, machine learning algorithms, and advanced AI applications.
| Level | Subjects / Learning Areas |
|---|---|
| Foundation Level | Introduction to Computer Science Fundamentals of Artificial Intelligence Introduction to Machine Learning Programming Fundamentals Python Programming Mathematical Foundations for AI Probability and Statistics Data Structures and Algorithms |
| Intermediate Level | Database Management Systems Data Analytics and Data Processing Exploratory Data Analysis Supervised Machine Learning Unsupervised Machine Learning Regression and Classification Feature Engineering Model Evaluation and Optimisation |
| Advanced Level | Artificial Neural Networks Deep Learning Fundamentals Natural Language Processing Computer Vision Reinforcement Learning Generative Artificial Intelligence Large Language Models AI Model Deployment Cloud Computing for AI Applications Responsible and Ethical AI |
| Practical Learning and Projects | Python-Based Data Analysis Predictive Analytics Projects Machine Learning Model Development Chatbot Development Image Classification Projects AI-Powered Application Development Final Capstone Project |
Note: The actual subjects, semester structure, credits, and practical components will depend on the university-approved curriculum.
Why choose it ?
Invest in a Future-Ready Skill Set
Choosing Artificial Intelligence and Machine Learning means exploring technologies that are changing how the world works. Develop knowledge that can help you adapt to digital transformation and participate in technological innovation.
- Future-Oriented Learning: Explore technologies that are influencing the future of business, education, healthcare, and communication.
- Industry-Relevant Curriculum: Understand important concepts, tools, and techniques used in AI and ML applications.
- Practical Exposure: Strengthen your understanding through assignments, coding exercises, and project-based activities, where included.
- Multiple Career Pathways: Explore opportunities across data science, software development, automation, and intelligent computing.
- Technology-Focused Education: Learn programming, algorithms, data processing, and intelligent system development.
- Flexible Learning Opportunities: Depending on the institution and programme mode, balance your education with personal and professional responsibilities.
- Innovation and Creativity: Develop the ability to approach challenges using intelligent and data-driven solutions.
- Continuous Skill Development: Build a foundation for exploring emerging technologies and advanced learning opportunities.
Don't Just Follow Technology – Learn How to Create It! Apply Now and Take Your First Step Towards an AI-Powered Future.
Learning Module
A Smart and Structured Learning Experience
Our learning approach is designed to make complex AI and Machine Learning concepts easier to understand through structured educational resources and progressive skill development.
Module 1 – Introduction to AI
Understand the history, concepts, applications, and importance of Artificial Intelligence in modern industries.
Module 2 – Programming with Python
Learn programming fundamentals, functions, libraries, data structures, and practical coding techniques.
Module 3 – Mathematics and Statistics
Build a foundation in linear algebra, probability, statistics, and mathematical concepts used in machine learning.
Module 4 – Data Science and Analytics
Explore data collection, cleaning, processing, analysis, and visualisation techniques.
Module 5 – Machine Learning Fundamentals
Understand different machine learning algorithms and learn how computers identify patterns from data.
Module 6 – Deep Learning
Explore neural networks, advanced learning methods, and deep learning applications.
Module 7 – Natural Language Processing
Understand text processing, language models, conversational systems, and intelligent chatbots.
Module 8 – Computer Vision
Explore image recognition, object detection, and visual intelligence applications.
Module 9 – Generative AI
Discover generative models, prompt engineering concepts, and applications of modern AI systems.
Module 10 – Industry Projects and Applications
Apply theoretical knowledge to practical projects and develop a portfolio demonstrating your technical capabilities.
Learn Step by Step, Build Real Skills, and Prepare for Emerging Technology Opportunities!
Examination Pattern
Evaluate Your Knowledge and Practical Understanding
The examination system is designed to assess students' conceptual understanding, analytical abilities, subject knowledge, and application of learned concepts. Depending on the university's academic regulations, the evaluation process may include:
| Assessment Type | Possible Evaluation |
|---|---|
| Internal Assessment | Assignments, quizzes, presentations, and periodic assessments. |
| Term-End Examinations | Assessment of subject knowledge and theoretical understanding. |
| Practical Assessment | Coding exercises, programming assignments, and laboratory activities, wherever prescribed. |
| Project Evaluation | Assessment of practical projects, case studies, and problem-solving abilities. |
| Continuous Evaluation | Monitoring academic participation and learning progress throughout the programme. |
Examination Highlights
- Assessment according to the prescribed university examination scheme.
- Subject-wise evaluation.
- Online or offline examination arrangements, as officially permitted.
- Results and academic progression according to university regulations.
Please note: The examination mode, marks distribution, passing criteria, and assessment schedule will be determined by the concerned university.
Approvals
Make an Informed Education Choice
Choosing a recognised and authorised educational institution is an important step towards achieving your academic and professional goals. Before enrolling, students should verify the following applicable recognitions and institutional credentials:
- UGC Recognition: Verify that the degree-awarding university is recognised by the University Grants Commission.
- UGC-DEB Entitlement: For an online or distance programme, verify the university and the specific programme's entitlement for the relevant academic session.
- AICTE Approval: Check whether AICTE approval or any other statutory approval is applicable to the specific programme and institution.
- NAAC Accreditation: Review the university's accreditation status and grade, where applicable.
- Other Statutory Approvals: Check relevant regulatory requirements, where applicable.
- University Recognition: Confirm that the institution is legally authorised to award the qualification.
Study with Confidence: Always verify the exact programme, specialisation, delivery mode, and academic session through official regulatory sources before taking admission.
Fee Structure
Quality Education with Transparent Fee Details
Take the next step towards your technology career with a clearly communicated fee structure and convenient payment information. We believe students should have access to transparent information about their educational investment before making an admission decision.
Fee Details
| Fee Component | Details |
|---|---|
| Registration Fee | As applicable. |
| Admission Fee | As prescribed by the university. |
| Tuition Fee | As per the selected programme. |
| Examination Fee | As per university guidelines. |
| Additional Charges | Applicable learning resources or other prescribed charges, if any. |
| Payment Options | Available payment methods as specified by the institution. |
| Installment Facility | Subject to the university's payment policy. |
What Students Should Know
- Get complete fee details before confirming admission.
- Understand semester-wise or annual payment requirements.
- Check applicable scholarships or fee concessions.
- Review examination and additional charges.
- Receive official payment confirmation and receipts.
Want to Know the Complete Fee Structure?
Connect with Our Admission Counsellor and Get the Latest Fee Details.
Placement Assistance
Turn Your Knowledge into Career Opportunities
Building technical knowledge is just the beginning. Developing career readiness, practical confidence, and professional skills is equally important.
The placement assistance support, where provided by the institution, aims to help eligible students prepare for employment opportunities in the technology sector.
Career Support Services May Include
Resume Building
Guidance to create a professional, skill-oriented resume.
Interview Preparation
Practice for technical and HR interviews.
Technical Skill Development
Support in improving programming, analytical, and problem-solving skills.
Career Counselling
Guidance to identify suitable job roles and career pathways.
Mock Interviews
Practice sessions to improve communication and interview confidence.
Job Opportunity Updates
Information about relevant job openings and recruitment opportunities.
Portfolio Development
Guidance on showcasing projects and technical achievements.
Professional Development
Support in improving workplace communication and presentation skills.
Potential Hiring Sectors
IT and Software Development • Artificial Intelligence and Automation • Data Science and Analytics • Banking and Financial Technology • Healthcare Technology • E-Commerce and Digital Businesses • Research and Technology Consulting
Get Career-Ready with the Right Skills, Practical Knowledge, and Professional Guidance! Placement assistance does not guarantee employment, a particular salary, or placement with a specific company. Opportunities depend on individual skills, qualifications, experience, and employer requirements.
Admission Process
Your Journey Towards an AI Career Starts Here
Getting started with your AI and Machine Learning education is simple. Follow these steps to complete the admission process.
- Explore the Program Understand the programme structure, eligibility requirements, duration, curriculum, and career opportunities.
- Check Eligibility Review the academic qualifications and admission requirements prescribed by the university.
- Submit the Application Form Complete the online admission application with accurate personal and educational details.
- Upload Required Documents Submit the necessary academic certificates, identity proof, photographs, and other requested documents.
- Verification Process The university or authorised admission department will verify your application and submitted documents.
- Pay the Applicable Fees Complete the prescribed admission and programme fee payment through the authorised payment channel.
- Confirm Your Admission Receive admission confirmation and registration details after successful completion of the university's admission formalities.
- Begin Your Learning Journey Access the applicable learning platform, study materials, academic schedule, and student support facilities.
Take the First Step Today – Apply Now and Start Building Your Future in Artificial Intelligence!
Required Documents
Keep Your Admission Documents Ready
To ensure a smooth admission process, applicants should keep the following documents ready.
| Document | Category |
|---|---|
| Class 10th Marksheet and Certificate | Educational document |
| Class 12th Marksheet and Certificate | Educational document |
| Graduation Marksheet and Degree Certificate, where applicable | Educational document |
| Previous Academic Qualification Certificates | Educational document |
| Transfer Certificate, if required | Educational document |
| Migration Certificate, if required | Educational document |
| Aadhaar Card or another accepted identity document | Identity & personal document |
| Recent Passport-Size Photograph | Identity & personal document |
| Scanned Signature | Identity & personal document |
| Valid Email ID | Identity & personal document |
| Active Mobile Number | Identity & personal document |
| Address Proof, if required | Identity & personal document |
| Category Certificate, if applicable | Additional document |
| Work Experience Certificate, if required | Additional document |
| Other supporting documents as prescribed by the university | Additional document |
Important: Document requirements may vary according to the programme, qualification level, and university admission guidelines.
STUDENT GUIDELINES
UGC Refund Policy
We encourage students to understand the applicable fee refund rules before confirming their admission. The University Grants Commission (UGC) has prescribed fee refund guidelines for eligible Higher Educational Institutions. Students withdrawing from a programme may be entitled to a refund depending on the date on which the institution receives their withdrawal request and the applicable academic session's policy.
1. Important Refund Guidelines
| Guideline 1 | Students should submit their admission cancellation or withdrawal request through the prescribed official process. |
|---|---|
| Guideline 2 | Refund eligibility is determined according to the applicable UGC policy and institutional regulations. |
| Guideline 3 | The percentage of refund depends on the date of withdrawal in relation to the formally notified last date of admission. |
| Guideline 4 | Applicable processing charges and permitted deductions will be governed by the relevant UGC guidelines. |
| Guideline 5 | Students should retain their fee receipts and official withdrawal acknowledgement. |
| Guideline 6 | Refunds will be processed within the applicable regulatory and institutional timelines. |
Our Commitment: We encourage transparent admission practices and clear communication of all applicable refund conditions so that students can make informed educational decisions.
Official document: View UGC Refund Policy (PDF)
Official document: View UGC Refund Policy (PDF)
Important: For the latest applicable refund rules, students should refer to the university's official refund policy and the UGC notifications for the relevant academic session. Visit the UGC Official Website for official notices and information.
Real Student Feedback
AI and Machine LearningReviews & Ratings
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Let’s clear up some doubts
How do I check whether AI and Machine Learning is recognised?
Value is more than the headline fee. Compare the depth of the curriculum, trainer access, practical projects, support, assessment and the credibility of the resulting qualification or certificate, where applicable.
What is worth confirming before paying for AI and Machine Learning?
Build a shortlist by checking the course content, prerequisites, format, time commitment, full cost and outcomes against your own priorities. Verify any claims about rankings, recognition or placement support from reliable current sources.
Can I fit AI and Machine Learning around my work or other commitments?
The topics can differ between providers. Read the current syllabus for AI and Machine Learning and look for the core modules, practical work, assessments and any elective choices. Treat a general course description as a starting point, not a substitute for the full curriculum.
What should I look for in the syllabus for AI and Machine Learning?
It may be possible, but the timetable matters. Before enrolling in AI and Machine Learning, check live-session timings, attendance rules, assignment deadlines and exam dates against your work and personal commitments.
How can I make a shortlist for AI and Machine Learning?
Ask for an itemised cost breakdown for AI and Machine Learning, including tuition, registration, examination, software, materials and any other compulsory charges. Confirm instalment dates, cancellation rules and refund terms before paying.
What practical outcomes could AI and Machine Learning help me work towards?
Recognition depends on the provider, qualification and intended use. Check relevant official regulator or accreditor records and, if needed, confirm acceptance with the employer, licensing body or institution where you plan to use the qualification.
Are there exams or assessments in AI and Machine Learning?
Some courses welcome beginners, while others assume prior study or professional experience. Check the prerequisite list for AI and Machine Learning and ask the provider whether preparatory learning is recommended if you are new to the subject.
What should I know before choosing AI and Machine Learning?
Ask how to contact faculty or trainers, access learning materials, get technical help and resolve academic questions. For online learning, also confirm whether sessions are recorded and how long you can access course resources.
How can I compare providers offering AI and Machine Learning?
Start with the exact outcome you want from AI and Machine Learning, then check the current course outline, entry rules, schedule and total cost. The title alone may not tell you what is included, so ask the provider to clarify anything important before you commit.
Can beginners apply for AI and Machine Learning?
There is no single duration that applies to every provider. Check the published study period, term or semester structure, pace options and any maximum completion window for AI and Machine Learning before planning your schedule.