AI-1: Basics of AI & ML

Standalone Course

This 5-week module is our first course in Machine Learning, and is designed to teach you the basics of supervised machine learning using models like linear and logistic regression.

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Starts

September 15, 2020
To be decided
Self-paced

Duration

5 Weeks

Format

Online-Live
Online

Fee

₹35,000

(Interest free EMI available)

Registration closes

September 10, 2020
To be decided

Program overview

This module will introduce you to basic statistical models such as linear and multi-linear regression and then move on to classification modeling with logistic regression. Finally, the course will provide a basic understanding of modern neural networks. Along the way, you will operationalize the key concepts of machine learning: picking the right complexity, preventing overfitting, regularization, and model evaluation. At the end of this module, you will be able to run basic machine learning models, and tell how well they are performing.

Who should apply

If you are someone who would like learn at your own pace, we make individual modules available for enrolment. We recommend that you take both AI-1 and AI-2 to round out your basic training in AI. With both these modules completed, you will have completed all the prerequisites necessary to take the Advanced Program in AI at a later date. The program requires prior experience in Python programming, and python libraries such as NumPY and Pandas. The program also requires you to be familiar with basic (high-school or first-year of college level) linear algebra and statistics. If you do not meet these prerequisites, then look up our 5-week Foundations Program.

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Course outcomes

Topics covered

  • kNN Regression and Linear Regression
  • Multi-Regression,  Poly-Regression, Model Selection using Train/Validation and Cross Validation
  • Inference in Linear Regression
  • Regularization: Ridge & Lasso Regressions
  • Logistic Regression, Loss Function for Logistic Regression, Multi+Poly Logistic Regression and Decisions Boundaries
  • Regularization for Logistic Regression, Multi-class Logistic Regression, Metrics and Data Imbalance, ROC curves, Precision, and Recall
  • Neural Networks 1 - Perceptron and MLP, Anatomy of Neural Networks and Design Choices
  • Neural Networks 2 - Fitting Neural Networks
  • Case study of a real-world problem - From beginning to end

Program Structure

Live online classes
1. Live Online Classes

Bi-weekly lessons with labs and quizzes

Mentorship
2. Mentor-Supported

Ten or more hours/week to interact with an experienced & accomplished mentor

Module end Project
3. End-of-Module Project

Complex problems that challenge you to apply what you learned

Capstone
4. Capstone

10–12 week long Capstone Project with one of our partner companies or faculty

Curriculum

Path
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Level 1
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ELECTIVES
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CApstone
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Download our Brochure

Not ready to enroll but want to learn more? Download the certificate brochure to review program details.

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Financial Assistance

Interest-free EMI

Interest-free EMIs are available for everyone. Apply easily through our banking partner once you complete the application process.

Scholarships for the best

Univ.AI Scholarships are available for the most promising candidates, based on performance in our application test, and your financial needs. Our scholarships will pay part of your tuition fee.

Income Sharing Agreement

Pay a sum equivalent to 30% your course fee at the start. After course completion, pay in instalments of 15% of your monthly salary for a period of 24 months to be free of any financial obligation to us. You payments are capped at the course fee (not including the sum paid upfront), or 24 months from your first payment, whichever happens earlier. Speak to a counsellor to determine eligibility.

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Tell a friend about our program

And we'll give you both Amazon vouchers worth ₹ 5,000

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Frequently asked questions

Who should take stand-alone modules?

If you cannot devote the time necessary to complete an entire program as per schedule and want to do it module by module. Or, if you need only some part of the curriculum, then you can only take classes for your personal learning objectives.

I have just taken AI-1 and AI-2. Can I directly join a capstone project or apply for a practice internship?

Project programs and Practice Internship Programs will be announced soon for candidates who have already completed requirements for them. You can apply for many of them if you have proficiency in the material taught in AI-1 and AI-2.

Can I take Univ.AI’s Advanced AI Programs after I complete AI-1 and AI-2?

Yes, you can. And you will also be eligible for direct admission without entrance exam to our Advanced AI Program.

Do I need to apply and take an entrance exam to take each module separately?

No, you do not. You can select a module and go straight to payment.

Do you advise taking stand-alone modules or complete programs?

By the virtue of their long-term association with the system, program students get better opportunities for company sponsored projects, paid consulting projects, research opportunities with top faculty around the world and more. If possible, we recommend that you take at least two modules one after the other, and then take a break. That will enable the system to help you better.

Is the financial assistance/scholarships available for individual modules?

No. However, do contact if you wish to participate and are unable to for reasons of financial hardship. Please be prepared to submit evidence of financial hardship if you wish to considered for hardship-based grants.

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