UGC Approved
AICTE Recognized
AIU Member
WES Member
Duration:
2 years (4 semesters)
Universities:
1 University
Fees:
26,500/-
per semester
Eligibility:
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Program Overview
The M.Tech in Machine Learning program provides an in-depth understanding of data and algorithms. Key topics include supervised and unsupervised learning, deep learning, and data mining. The curriculum features practical lab sessions, real-world projects, and industry internships for hands-on experience. Advanced subjects such as natural language processing, computer vision, and big data analytics are also covered. The program addresses ethical and legal issues related to AI. Students will develop strong programming and analytical skills, preparing them for dynamic careers in technology and data science.
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- Educational Qualification: A bachelor’s degree in Mechanical Engineering or a related field, typically with a minimum 50%
- Entrance Exam: Some institutions require you to pass a relevant entrance exam. Common exams include:
- GATE (Graduate Aptitude Test in Engineering): Widely accepted by many institutions in India.
- Institution-specific Entrance Tests: Some universities or institutes may have their own entrance exams.
Per semester 26,500/- (fee might vary university to university)
Minimum 2 years and Maximum 4 years program
- Programming Skills:
Develop proficiency in programming languages like Python, essential for implementing machine learning algorithms. - Research Opportunities:
Engage in cutting-edge research projects and develop a thesis on a specific machine learning topic. - Analytical Skills:
Enhance your ability to interpret and analyze complex data effectively. - Collaborative Projects:
Improve teamwork and communication skills through collaborative projects and exercises. - Industry-Relevant Curriculum:
Stay updated with the latest industry trends and technologies. - Problem-Solving Skills:
Build strong problem-solving skills through various practical assignments and projects. - Innovation and Creativity:
Foster innovation and creativity through research and project work. - Career Preparation:
Prepare for diverse career paths in technology, data science, and AI with a well-rounded education.
- Programming Proficiency:
Focus on programming skills, especially in Python. - Research Opportunities:
Involvement in research projects and thesis work. - Analytical Skills:
Development of strong analytical and problem-solving abilities. - Collaborative Learning:
Emphasis on teamwork through group projects and exercises. - Up-to-Date Curriculum:
Aligned with current industry trends and advancements. - Innovation Encouraged:
Opportunities to engage in creative and innovative work. - Career Readiness:
Preparation for a variety of roles in technology and data science fields.
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Course Syllabus
Duration: 2 years (4 semesters)
Rating: 4.2/5
4 Credits Per Subject
Key Role of M.Tech
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Admission Procedure
Online Form
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Enrollment
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Pay
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Our Alumini
CIIS has the most dedicated staffs, they were very patient enough to answer my never ending queries. They are very experienced in handling and guiding their students !! It was the most pleasant experience and journey with them. Looking forward to collaborate for another enriching student’s experience with CIIS. Thank you all.
FAQs
Let’s Clear Your Doubts
CIIS is pioneer leading organization to provide Distance Education across world and traditional regular courses in India. We are imparting education to thousands of students and working professionals in India through various UGC, AICTE, Ministry of HRD Govt. of India approved national and internationally acclaimed Universities.
Courses on AI ethics and legal frameworks are included to cover the societal and regulatory aspects of machine learning technology.
Internships offer practical experience and exposure to industry practices, often involving real-world machine learning projects.
Graduates can pursue roles such as machine learning engineer, data scientist, AI researcher, and various other positions in technology and data science.
Yes, the program offers specializations in areas like natural language processing, computer vision, and big data analytics.
The application process typically involves submitting an online application form, academic transcripts, letters of recommendation, a statement of purpose, and possibly standardized test scores (like GATE).
Some institutions may offer online or part-time options, but this varies by program and institution. Check with specific universities for availability.
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