Switchup: TRANSFORM YOUR CAREER

Transition to AI/ Machine Learning Engineering roles at Tier-1 companies

Designed and taught by FAANG+ AI/Machine Learning Engineers to help you transform your career and land your dream job.

Criteria: 5+ yrs work exp. No ML exp required.

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Students who chose to uplevel with IK got placed at

Akshay Lodha

Data Engineering & Analytics

Anju Mercian

Data Engineering Consultant

Alokkumar Roy

Data Engineer

Siva Karthik Gade

SDE, Machine Learning

Sai Marapa Reddy

SWE, Machine Learning

Safir Merchant

SWE, Machine Learning

Jameson Merkow

Principal AI Engineer

Sayan Banerjee

Data Scientist II

Mike Kane

Lead Data Engineer, Analytics

17K+

Tech professionals trained

53%

Average salary hike received by alums

AI/Machine Learning Course Curriculum

PART 1: Mastering Machine Learning

Foundations

Python Fundamentals

Variables, if-else, loops, Functions, lists, strings, etc. related coding examples
Tuples, Set, Dict, map, filter, reduce etc. related coding examples
OOP in Python, File and Exception handling
Numpy, Pandas, etc.
Visualisation with Python

Software Development Essentials

Scripting, Git & GitHub
Databases & Intro to SQL

Essential Mathematics for Machine Learning

Essentials of Probability

Probability Distribution

Essentials of Statistics

Hypothesis Testing

Basic and Linear Algebra

Calculus

Vectors and Matrices

Regression

Deep Dive into Machine Learning Engineering

Foundational Machine Learning Concepts

Data Pipelines for ML: Techniques and Best Practices
Supervised Machine Learning Techniques and Applications
Unsupervised Machine Learning Techniques and Applications
Introduction to Neural Networks and Deep Learning Architectures such as RNN, LSTM, CNN etc
AI Development through Multiple Mini Projects: Hands-on Techniques and Applications

Advanced Machine Learning Framework: Techniques and Best Practices for Successful Development

NLP: Techniques and Applications of Natural Language Processing using Embeddings, Autoencoders, VAE, GANs etc.
Generative AI : BERT, Transformers, and LLMs for Advanced AI Development
Computer Vision Techniques and Applications in AI for Image and Video Analysis : Object Detection, Boundary Detection, Image Segmentation etc
Reinforcement Learning through Human Feedback (RLHF) : Introduction and Applications in Generative AI.
Deep Learning Mini Projects: Hands-on Techniques and Applications to build a system from scratch.

ML Development and Deployment: Advanced ML and MLOps Techniques

Software System Design Fundamentals: Principles and Best Practices for AI-based Development
ML Design Principles: Guiding principles for developing effective ML systems.
Scoping ML Projects: Defining goals, objectives, and boundaries of ML projects
Distributed Training: Data & Model Parallelism using GPUs
Model Deployment: Best Practices for Successful Implementation and Maintenance at Scale
Improving Model Performance: Techniques and Strategies for Retraining and Model Decay
AI Model Monitoring and Maintenance: Best Practices for Ensuring Optimal Performance
Failure Analysis: Techniques and Strategies for Diagnosing Production Issues
Ensuring ML Model Stability: Techniques and Best Practices

Capstone Project: Real-world Applications and Hands-on Experience in Machine Learning

Industry-Relevant AI Projects: Techniques and Best Practices for Developing Real-world Solutions
AI Mentorship at FAANG Companies: Techniques and Best Practices for Career Development
Capstone Presentation: Best Practices for Presenting Machine Learning Solutions to Stakeholders

PART 2: Interview Preparation

Data Structures and Algorithms Interview Preparation

Trees

Graphs

Greedy Algorithms

Dynamic Programming

Software System Design Interview Preparation

Online Processing Systems

Batch Processing Systems

Stream Processing Systems and Object Modeling

AI/Machine Learning Interview Preparation

Supervised Learning I - Rank Relevant Search Results

Supervised Learning II - Design a YouTube Video Recommendation System

Unsupervised Learning - Detect Fraud Transactions for Airbnb

Deep Learning I - Detect and Process Objects in a Scene

Deep Learning II - Build a Tech Support Chatbot

Additional Topics:

Comprehensive, Step-by-Step Approach to ML System Design Interviews
Modern ML Architectures
Reinforcement Learning

Career & Behavioral Sessions

Interview strategy and success

Behavioral interview prep

Offers and negotiation

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Best suited for

Why choose this course?

Program by FAANG+ ML Engineers

360° course designed and taught by FAANG+ experts to help you become an ML Engineer

Individualized teaching and 1:1 help

Technical coaching, homework assistance, solutions discussion, and individual sessions

Capstone project

Exposure to real-life machine learning projects

Interview prep modules

Dedicated interview prep classes focused on helping you get 100% interview-ready

Mock interviews with FAANG+ ML Engineers

Live interview practice in real-life simulated environments with FAANG and top-tier interviewers

Career skills development

Resume building, LinkedIn profile optimization, personal branding, and live behavioral workshops

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Meet your instructors

Our highly experienced instructors are active hiring managers and employees at FAANG+ companies and know exactly what it takes to ace tech and managerial interviews.

Matt Nickens

Manager, Data Science

10+ years experience

Jameson Merkow

Principal AI Engineer

11+ years experience

Christian Monson

Machine Learning Scientist

9+ years experience

Alireza Dirafzoon

Research Engineer

7+ years experience

Anmol Darak

Data Scientist II

10+ years experience

Rituraj Jodha

Senior Data Scientist

10+ years experience

Mantej Gill

AI Researcher and Senior ML R&D Engineer

10+ years experience

Abhinav Maurya

Data and Applied Scientist 2

10+ years experience

Shubajit Saha

Software Engineer Machine Learning

10+ years experience

Built for working professionals

Here’s what a typical week would look like:

Sunday

4-hour Live Classes in the morning

Thursday

2-hour session in the evening to discuss assignments and problem solutions

Once a week

1-hour technical coaching session to discuss any additional doubts

Practice and track progress on UpLevel

Designed and taught by FAANG+ AI/Machine Learning Engineers to help you transform your career and land your dream job.

Mock interviews suite

On-demand timed tests

In-browser online judge

10,000 interview questions

100,000 hours of video explanations

Class schedules & activity alerts

Real-time progress update

11 programming languages

Get upto 15 mock interviews with

hiring managers

What makes our mock Interviews the best:

Hiring managers from Tier-1 companies like Google & Apple

Interview with the best. No one will prepare you better!

Domain-specific interviews

Practice for your target domain - Machine Learning

Detailed personalized feedback

Identify and work on your improvement areas

Transparent, non-anonymous interviews

Get the most realistic experience possible

More about mock interviews

1. Flexible schedule

Pick timings convenient to you

4. Technical and behavioral interviews

Uplevel your technical and behavioral interview skills

2. Remote interview experience

Mirrors the current format of remote interviews

5. Level-specific interviews

Because an L4 at Google can be quite different from an E7 at Meta

3. Feedback documentation

All the feedback you’ve ever wanted, recorded and documented

6. Interviewer of your choice

Choose based on domain

Career impact

Our engineers land high-paying and rewarding offers from the biggest tech companies, including Facebook, Google, Microsoft, Apple, Amazon, Tesla, and Netflix.

Jameson Merkow

Principal AI Engineer

Placed at:

I joined IK because I had a lot of really terrible experiences with interviews. The confidence and expertise I routinely demonstrated in the workplace was not translating to interviews. I lacked confidence during behavioral interviews and felt completely lost when asked coding questions. IK taught me how to clearly demonstrate my skills and experience during interviews which ultimately helped me find a Principal engineering position at Microsoft.

Safir Merchant

Machine Learning Software Engineer

Placed at:

I liked the course that IK provided a lot. IK provided all the knowledge on a variety of topics that helped me prepare for coding interviews. The mock interviews were really great. Landing a job at my desired company has been a great pleasure.

Siva Karthik Gade

SDE — Machine Learning

Placed at:

IK offers high-quality study material, knowledgeable and patient instructors working at industry-leading companies, well-paced live classes + tests + review sessions, always available technical + career coaches, mock interview support from the best interviewers in the respective fields. IK brings together people with same the ambition (on their platform, UPLEVEL) to guide and inspire each other

Sai Marapa Reddy

SWE, Machine Learning

Placed at:

I completed IK’s program and got offers from a couple of FAANG companies. Why you should take this course: It is well tested and the focus is more on the concepts/templates rather than approaching one problem at a time. You will meet peers who have similar aspirations. You can make groups and help yourselves.

How to enroll for the Machine Learning Course?

Learn more about Interview Kickstart and the Machine Learning Course by joining the free pre-enrollment webinar.

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