

Diploma in Machine Learning at CIMT College Overview
CIMT College offers courses at PG level. The course lasts for a duration of 16 weeks. It is among the top-ranked courses in the country. To be eligible for the course, the students must fulfil the eligibility criteria, which includes valid score in exams such as IELTS, TOEFL and PTE. The CIMT College tuition fee for Diploma in Machine Learning for the first year is CAD 13,000. Also, the students have to make budget for the other costs which includes
- Rent
- Hostel fees
- Food
- Books
- Supplies
- Utilities, etc.
Duration | 16 weeks |
Tuition & Fees | ₹8.18 Lakh Get Fees details |
International Students Admission Website | Go to Website |
Official Career Service Website | Go to Website |
Course Level | PG Diploma |
Diploma in Machine Learning at CIMT College Fees
When planning for the Diploma in Machine Learning, applicants should consider the financial aspects involved. Every student must pay the first-year tuition fee of CAD 13,000. Additionally it is also important to account for living expenses such as accommodation, food, and utility costs. Such expenses may vary according to living styles and other fees added by the CIMT College. To know about the complete breakdown of the CIMT College Diploma in Machine Learning fee structure and all other cost-element-wise expenditures for an elaborate cost overview, please check the table below.
| Fees components | Amount (for 1 year) |
|---|---|
| Tuition & fees | INR 8,18,090 |
| Fees components | Amount (for 1 year) |
|---|---|
| Application fee | INR 31,465 |
| Total approximate fees | INR 31,465 |
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Diploma in Machine Learning at CIMT College Entry Requirements
- No specific cutoff mentioned
- Post Secondary Diploma/Degree or equivalent.
- Basic Knowledge of computers is preferred

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Out of 10
- Marks - 80/120
- NA
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- Marks - 50/90
- NA

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Out of 10
- Marks - 5.5/9
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Diploma in Machine Learning at CIMT College Highlights
- MACHINE LEARNING program provides students with a broad knowledge in two main areas of Machine Learning: supervised and unsupervised
- The program introduces to systems that learn from experience and outline the problems based on classification, clustering and regression
- It will cover topics Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines, Ensemble Learning with Bagging and Boosting, Random Forest , k-NN, Dimensionality Reduction, Principal Component Analysis, K-means algorithm, Self-Organizing Feature Maps, Apriori algorithm, FP-growth algorithm, Dimensionality Reduction using Principal Component Analysis, Anomaly Detection and Semisupervised Learning
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Diploma in Machine Learning at CIMT College Contact Information
2650 Slough Street
Mississauga, Ontario L4T 3T2
Mississauga ( Ontario)




