AI Career Fellowship (MLOps)

According to a report, 

“Only 22% of companies using machine learning have successfully deployed a model.”

More often than not, Data scientists are not expert programmers. While they might be extremely skilled at determining or developing the optimal model to solve a machine learning problem, they often lack the skills to package, test, deploy and maintain their models in a production environment. This is exactly where MLOps comes into play. MLOps essentially builds the bridge between Data Engineering, Machine Learning, and DevOps allowing you to integrate robust and reliable machine learning pipelines.

Top jobs in AI today are no longer focused just on pure machine learning practices. Instead, data engineering and cloud skills are becoming more and more critical for managing the whole machine learning lifecycle thus increasing the need for experts.

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Program image

Starts

April 30, 2023

Duration

8 weeks

Time Investment

10 Hrs/Week

Format

Live, Online

Fee

$0 ($100 processing fee)
₹0 (*small processing fee upon selection)

Registration closes

April 16, 2023

What do you get being a part of the Fellowship?

Mentored preparation for top global careers
Image of a handshake
5 times every week for 6 weeks of fun & high engagement with peers from reputed institutions & organizations
Participation in Univ.AI's global placement system for employment opportunities worldwide
Interactions with top faculty and professionals during guest sessions

Meet the teaching team

Course Outcome

Who should apply

This program is ideal for advanced AI practitioners with a good command on building deep learning models, who seek top, well compensated positions in the field.

Split into three parts; the course starts with the Review of Deep Learning concepts for data and modeling and how to apply them to different tasks, including vision and language tasks. The next part will be Development, where you use the models you trained in part 1 and incorporate them into real-world applications. Finally, you will Deploy the application in Google Cloud Platform (GCP). The three parts will cover in detail topics such as Transfer learning, Containerization using Docker, and Scaling deployments using Kubernetes.

Prerequisites

Your are expected to know the following:

  • Good working knowledge of python
  • Good understanding on the Tensorflow Deep Learning framework
  • Basic shell commands

Programming:

  • Experience with Python: Functions, Classes, Modules, NumPy, Pandas, Tensorflow
  • Basic Data Structures: Dictionaries and Lists
  • File I/O

Class Timings

Classes - Saturday [ 11:00 AM - 01:00 PM EST ] [ 8:00 AM - 10:00 AM PST ] 

Office hours - Tuesday [ 11:30 AM - 12:30 PM EST ] [ 8:30 AM - 10:30 AM PST ]

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Fellowship Structure

Live online classes
1. Live Online Classes

Bi-weekly live, cohort-based 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 learn

Topics Covered

AI-5

  • Introduction, Models, Projects
  • Virtual environment & Virtual machines
  • Containers, cloud functions
  • Data pipelines, Dask, Cloud storage
  • TF data, TF records
  • App design, Setup and Code organization
  • API, Frontend and Deployment
  • Scaling & Automation

Policy

Cost of attending the fellowship

We charge a tiny processing fee of USD-100 for the 8-week LIVE program toward processing cost.

Total initial amount - USD 100 payable upon acceptance.

The charge is for the cost of the platform, EdStem, for which we pay on a per-seat basis. Compute, also a significant per-person cost is currently provided free.

POLICY for the Certificate

- 75% attendance 

- All submissions (Homework + Projects)

You will need to pay two small amounts:

  1. A fully-refundable skin-in-the-game deposit of Rs, 3500*
  2. A non-refundable, pass-through Edstem (platform) fee of Rs. 1500.

Total initial amount - Rs. 5000 of which Rs. 3500 is fully refundable*

The non-refundable charge is for the cost of the platform, EdStem, for which we pay on a per-seat basis. Compute, also a significant per-person cost is currently provided free.

*REFUND POLICY for the refundable portion of the fee

- 75% attendance 

- All submissions (Homework + Projects)

Why is there a fee for attending the fellowship

We charge a token fee merely to have your skin in the game. We’d like for you to attend once accepted. If you do not attend, someone else will be denied the opportunity.

Just so you know, the nominal value of the fellowship is around Rs. 90,000 per person for a 8 week program. This cost comes from the enormous amount of resources and costs, that go into making this opportunity available to a select few - namely

  • Professors & TAs
  • LMS platform
  • (EdStem)Curriculum development
  • Cloud compute & other cloud resources
  • A team of 40 people that supports various aspects of your experience

We charge a token fee merely to have your skin in the game. We’d like for you to attend once accepted. If you do not attend, someone else will be denied the opportunity.

Just so you know, the nominal value of the fellowship is around Rs. 50,000 per person for a 5-6 week program. This cost comes from the enormous amount of resources and costs, that go into making this opportunity available to a select few - namely

  • Professors & TAs
  • LMS platform
  • (EdStem)Curriculum development
  • Cloud compute & other cloud resources
  • A team of 40 people that supports various aspects of your experience

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