Learn Generative AI and Transition to Tier-1 Companies

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

Customized learning modules for:

Live Online Classes | Interview Prep | 1:1 Career Support

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Instructors, Coaches & Interviewers from Top Companies

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Students

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Avg. Salary Hike for Alums Who
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Tools you’ll learn

Interview Kickstart EdgeUp—Gain the AI Edge & Boost Your Career

Back-end Engineers

4.5

Front-end Engineers

4.6

Full-stack Engineers

4.7

Test Engineers

4.8

Product Managers

4.8

Engineering Managers

4.7

Technical Program Managers

4.7

Machine Learning Engineers

4.6

Data Scientists

4.6 Why EdgeUp?

Many companies have started adding Generative AI skills to job descriptions of several tech roles. We analyzed more than 10,000 JDs and found that over 10% of the roles now require GenAI skills, to be able to leverage the power of GenAI and improve productivity, efficiency, and creativity. Here are our findings:

GenAI-enabled Job Descriptions & skills

GenAI Skills Back-end Engineers Need Today

Python Proficiency: Understand Python and neural networks.
AI Integration: Leverage Generative AI in development.
Automation: Use AI for task automation.
Code Generation: Employ AI for coding.
Debugging: Enhance debugging with AI.
Testing: Improve testing via AI.
Innovation: Create novel AI-driven applications.
Feature Integration: Integrate AI features into tech stacks.
Architecture Knowledge: Understand AI architectures and types.‍
Project Planning: Stay relevant in AI project planning.

GenAI Skills Front-end Engineers Need Today

Python Basics: Understand Python and neural networks.
AI Integration: Utilize Generative AI in development.
Automation: Automate tasks with AI.
Code Generation: Leverage AI for coding.
Debugging: Enhance debugging processes.
Testing: Improve testing with AI.
UI/UX Innovation: Innovate user interfaces using AI.
Feature Integration: Integrate AI features into front-end projects.
Performance Optimization: Use AI to optimize performance.
Architecture Knowledge: Understand AI architectures and capabilities.

GenAI Skills Full-stack Engineers Need Today

Python Basics: Understand Python and neural networks.
AI Integration: Leverage Generative AI in development.
Automation: Automate tasks with AI.
Code Generation: Use AI for coding.
Debugging: Enhance debugging processes.
Testing: Improve testing efficiency.
Innovative Applications: Create novel AI-driven applications.
Feature Integration: Integrate AI features into tech stacks.
Performance Optimization: Optimize performance using AI.‍
Architecture Knowledge: Understand AI architectures and capabilities.

GenAI Skills Test Engineers Need Today

LLM Implementation: Test applications using LLMs.
Neural Network Knowledge: Understand various neural architectures.
Model Behavior: Identify model failure points.
Language Models: Grasp intricacies of language and generative models.
Transformers: Understand transformer mechanisms.
Scenario Creation: Generate diverse test scenarios with AI.
Regression Testing: Enhance regression testing efficiency.
Focus on Complex Tasks: Prioritize tasks requiring human intuition.
Model Size Knowledge: Understand model size and training data implications.‍
Scalability Monitoring: Test scalability and efficiency of AI models.

GenAI Skills Product Managers Need Today

AI Knowledge: Understand generative AI basics and limitations.
User Experience: Enhance experiences through automated content and personalized interactions.
Strategic Use: Deploy AI for competitive advantages and market opportunities.
Integration: Integrate AI in product development.
Communication: Collaborate effectively with technical teams.
Impact: Evaluate AI’s effect on user interfaces.
Ethics: Ensure ethical AI use and compliance.

GenAI Skills Engineering Managers Need Today

Feasibility Assessment: Assess technical feasibility and ROI of GenAI projects.
Market Trends: Understand trends and competitive advantages.
Project Prioritization: Prioritize projects aligned with business goals.
Team Management: Break down AI features and assign tasks.
Challenge Understanding: Grasp AI implementation challenges and timelines.
Innovation Potential: Recognize GenAI’s potential for problem-solving.
Project Lifecycle: Manage AI projects from data collection to deployment.
Technical Guidance: Provide technical guidance on GenAI projects.
Experimentation: Explore and run small-scale AI experiments.
Evaluation Skills: Evaluate LLMs and market offerings for build-vs-buy decisions.

GenAI Skills Technical Program Managers Need Today

Risk Management: Simulate and prepare for project risks with GenAI.
Risk Assessment: Use LLMs to assess project health and identify risk patterns.
Technical Understanding: Grasp GenAI fundamentals and technical challenges.
AI Planning: Plan AI models, timelines, and associated risks.
Experimentation: Conduct and convert AI experiments into production solutions.
Automation: Automate project scheduling, resource allocation, and task prioritization.
Routine Monitoring: Automate monitoring and reporting tasks.
Strategic Focus: Free up time for strategic planning.
Insight Generation: Generate GenAI-enabled insights for project adjustments.‍
Enhanced Accuracy: Improve analysis accuracy with AI.

GenAI Skills ML Engineers Need Today

Advanced Model Development: Create innovative AI models.
Problem Solving: Solve complex problems with GenAI.
State-of-the-Art Projects: Work on cutting-edge AI technologies.
Job Market Competitiveness: Enhance employability with advanced skills.
Efficiency: Improve workflows via automation and synthetic data generation.
Model Performance: Enhance models with fine-tuning and transfer learning.
AI-Driven Solutions: Develop AI that understands/generates text, images, audio.
Stay Current: Keep skills updated with latest GenAI advancements.
Resource Optimization: Reduce computational costs with AI optimizations.‍
Security and Ethics: Mitigate biases and vulnerabilities in models.

GenAI Skills Data Scientists Need Today

Model Innovation: Develop advanced AI models.
Automation: Automate data preprocessing and feature engineering.
Data Augmentation: Generate synthetic data for training.
Model Improvement: Enhance models with fine-tuning and transfer learning.
AI Solutions: Create AI-driven applications (chatbots, recommendation systems).
Productivity: Boost efficiency with AI-driven workflows.
Optimization: Optimize model performance and scalability.
Ethics and Security: Mitigate biases and vulnerabilities.
Decision-Making: Improve decisions with AI-driven insights.‍
Competitive Edge: Stay current with AI advancements for market competitiveness.

Detailed Curriculum

Back-end Engineers

GenAI Curriculum

Python Crash Course

Hands-on with Generative AI

Understanding Gen AI Architecture

Building Applications & Use Cases

Gen AI for Software Engineers Specialization & Capstone Projects

Capstone Projects

Back-end Engineering Interview Prep

Data Structure & Algorithms

Scalable System Design

Database Design & Object Modelling

API Design & Cloud Native Design

Concurrency

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Front-end Engineers

GenAI Curriculum

Python Crash Course

Hands-on with Generative AI

Understanding Gen AI Architecture

Building Applications & Use Cases

Gen AI for Software Engineers Specialization & Capstone Projects

Capstone Projects

Front-end Engineering Interview Prep

Data Structure & Algorithms

Scalable System Design

JavaScript Language & Libraries, UI & DOM

Front-End System Design

Advanced JavaScript and CSS

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Full-stack Engineers

GenAI Curriculum

Python Crash Course

Hands-on with Generative AI

Understanding Gen AI Architecture

Building Applications & Use Cases

Gen AI for Software Engineers Specialization & Capstone Projects

Capstone Projects

Full Stack Engineering Interview Prep

Data Structure & Algorithms

Scalable System Design

Database, API Design and Implementation

Cloud Infrastructure, JavaScript and Web Development

UI System Design

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Test Engineers

GenAI Curriculum

Python Crash Course

Hands-on with Generative AI

Understanding Gen AI Architecture

Building Applications & Use Cases

Gen AI for Software Engineers Specialization & Capstone Projects

Capstone Projects

Test Engineering Interview Prep

Data Structure & Algorithms

Scalable System Design

Quality Engineering Foundations, Performance Testing

API Testing, Automation Testing

Test Automation Design Patterns, Cloud Testing

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Product Managers

GenAI Curriculum
Self-paced learning videos on Python basics, Jupyter Notebooks and Google Colab, and ML Essentials available for those who want to learn from scratch

Fundamentals of Python I

Evolution of AI

Fundamentals of Python II

Hands-on with AI Models

Deep Dive into AI for Text Generation

Building AI Applications with Language Models

Training AI Models for Text Generation

Guided Live Project 1- Deploying AI Models with Streamlit

Guided Live Project 2 - Building AI Financial Bot

AI For Image Generation

Guided Live Project -3 - Linkedin Headshot App

GenAI for Audio/Guided Live Project 4 - Audio Synthesis with AI

Capstone Projects - Product Management Focus

Personalized Sessions for Product Managers

Capstone Projects

Product Management Interview Prep

System Design for PMs

Product Sense: Planning, Design, Estimation, Strategy

Product Execution: Pricing, Design, Improvement and Growth

Technical: Analytics, Metrics, Technical Concepts, Process Analysis

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Engineering Managers

GenAI Curriculum
Self-paced learning videos on Python basics, Jupyter Notebooks and Google Colab, and ML Essentials available for those who want to learn from scratch

Fundamentals of Python I

Evolution of AI

Fundamentals of Python II

Hands-on with AI Models

Deep Dive into AI for Text Generation

Building AI Applications with Language Models

Training AI Models for Text Generation

Guided Live Project 1- Deploying AI Models with Streamlit

Guided Live Project 2 - Building AI Financial Bot

AI For Image Generation

Guided Live Project -3 - Linkedin Headshot App

GenAI for Audio/Guided Live Project 4 - Audio Synthesis with AI

Capstone Projects - EM Focus

Personalized Sessions for Engineering Managers

Capstone Projects

Engineering Management Interview Prep

Scalable System Design

Career & Leadership workshops

Coding

Technical Domain Course (DE/ML/DS/ES/FE/BE/FSE/SRE/Cloud/Android/iOS/Security)

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Technical Program Managers

GenAI Curriculum
Self-paced learning videos on Python basics, Jupyter Notebooks and Google Colab, and ML Essentials available for those who want to learn from scratch

Fundamentals of Python I

Evolution of AI

Fundamentals of Python II

Hands-on with AI Models

Deep Dive into AI for Text Generation

Building AI Applications with Language Models

Training AI Models for Text Generation

Guided Live Project 1- Deploying AI Models with Streamlit

Guided Live Project 2 - Building AI Financial Bot

AI For Image Generation

Guided Live Project -3 - Linkedin Headshot App

GenAI for Audio/Guided Live Project 4 - Audio Synthesis with AI

Capstone Projects - TPM Focus

Personalized Sessions for Technical Program Managers

Capstone Projects

Technical Program Management Interview Prep

Scalable System Design

Program Planning, Execution, Monitoring & Reporting

Behavioral — Introducing Frameworks, Cross-Functional Cooperation, Motivation and Core Values

Technical Domain Course (DE/ML/DS/ES/FE/BE/FSE/SRE/Cloud/Android/iOS/Security)

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Machine Learning Engineers

Advanced GenAI Curriculum

Deep Learning Primer, Neural Architectures, Gen AI: Background

Deep-Dive into LLMs, LLMs in Production

Diffusion Models, Multimodal Models

Reinforcement Learning from Human Feedback

Capstone Project

Capstone Projects

ML Engineering Interview Prep

Data Structure & Algorithms

Scalable System Design

Supervised Learning - Rank Relevant Search Results, Design a YouTube Video Recommendation System

Unsupervised Learning - Detect Fraud Transactions for Airbnb

Deep Learning - Detect and Process Objects in a Scene, Build a Tech Support Chatbot

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Data Scientists

Advanced GenAI Curriculum

Deep Learning Primer, Neural Architectures, Gen AI: Background

Deep-Dive into LLMs, LLMs in Production

Diffusion Models, Multimodal Models

Reinforcement Learning from Human Feedback

Capstone Project

Capstone Projects

Data Scientist Interview Prep

Data Structure and Algorithms

SQL Programming

Probability, Distributions

Data Science Design: A/B testing, Regression, MLE, EM, and MAP

Supervised & Unsupervised Machine Learning

Deep Learning, Time Series Analysis

Career Sessions: Mock Interviews, Feedback Sessions

Support Period

Other Tech Professionals

GenAI Curriculum

Python Crash Course

Hands-on with Generative AI

Understanding Gen AI Architecture

Building Applications & Use Cases

Capstone Projects

General Tech Projects

AI Customer Service Agent

Design an LLM-based customer service agent capable of understanding and responding to customer queries in natural language, which can handle real-time customer interactions

AI Personal Shoppe

Create a personalized shopping assistant application using OpenAI’s GPT-3.5 or a similar LLM, which can engage with customers through natural language, understanding their preferences, budget, and needs to recommend products they’ll love.

Software Engineering Projects

Intelligent Virtual Assistant for Developers

Develop a virtual assistant for software developers that can understand complex programming queries, offer coding advice and debug tips, and even write small code snippets using LLM APIs.

Intelligent Meeting Summarizer

Develop a tool that leverages LLMs to provide summaries and action items from virtual meetings. This app can transcribe conversations, highlight key points, and list tasks, saving time and ensuring that important details are captured and actioned upon.

Product Management Projects

AI Product Strategies, Roadmaps & Execution

Recommend user experience improvements and suggest new product features that leverage Generative AI, and create PRD/Product Strategies to integrate AI into existing products.

Technical Program Management Projects

Gen AI Project Lifecycle—Strategy to Execution

Develop a case study on the business integration of GenAI, detail the project management strategies used, analyze AI integration within existing systems, and include insights on ethical practices and regulatory compliance.

Engineering Management Projects

AI-Driven Engineering System Enhancement

Redesign an existing engineering system to seamlessly integrate Generative AI, emphasizing the enhancement of engineering efforts through automated decision-making, and evaluate tech stack modifications and scalability.

General Tech Projects

AI-Powered Resume Coach

Develop a Resume Coach that will analyze a user’s resume and compare it to job descriptions and industry standards, providing constructive and personalized feedback and suggestions based on successful resumes in the field.

Conversational Shopping Assistant

Create an AI assistant that understands detailed requests, and is able to provide precise product suggestions in real-time user interactions, and is able to respond in natural language.

+ Instructors to Train You in Live Classes

Randy Cogill

Senior Research Scientist

Jay Pillai

Engineering Leader - GenAI

FAANG+ Leader

Shruti Goli

Senior Product Manager, Incode

Ahsan Ali

Applied Scientist

Learn more about the course & pricing

It's Free

The IK Experience: What Our Alumni Are Saying

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

Mike Kane

Senior Software Engineer

Placed at:

My experience at IK was extremely positive. I was preparing for FAANG companies using the standard techniques that you find on the internet. When I started preparing, there was no structure to the madness. For example, a simple quicksort can be implemented in multiple ways. So solving a medium problem would take me about 30 minutes. The biggest benefit that I got from IK was a clear, structured way of solving problems. After IK, I could solve medium problems in 10 minutes!

Davide Testuggine

Software Engineer

Placed at:

What turned me to Soham’s course is the way he talked about the course as not a substitute for hard work, not a “cheat sheet” of questions but a way to actually get good at algorithms, through a lot of perspiration. The course is very intense…practice, practice, practice. And it works!.... All that practice had a long-lasting effect on my ability as a software engineer. I am simply faster at coding than I ever was…. I can keep focused on the idea if the implementation takes a few minutes as I don't get lost on implementation details anymore, so the productivity increase I experienced is greater than just the delta in time for the implementation itself.

Get upto 15 mock interviews with hiring manager

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 - Back-End Engineering

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

How to Enroll for Interview Kickstart’s EdgeUp Program

Learn more about Interview Kickstart and the EdgeUp Program by joining the free pre-enrollment webinar.

Learn more about the course & pricing

It's Free

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FAQs

What is the Interview Kickstart EdgeUp Program?

Interview Kickstart’s EdgeUp Program is a unique course designed to equip you with Generative AI skills relevant to your domain and job role AND prepare you for interviews at top tech companies. You will not only gain the skills required to stay relevant in today’s AI-drien techworld, but also be ready to ace interviews to land your dream job.

How does the EdgeUp program work?

EdgeUp is a combination of Applied Generative AI and our industry-acclaimed interview prep programs. You will first spend around 14 weeks training on Generative AI and learning the practical applications of it in your domain, and spend another 12-16 weeks on interview preparation that incorporates both your current domain and Generative AI integration.

Will the EdgeUp Program help me get better jobs?

Yes. The first half of this program will be about building GenAI literacy and technological fluency for creative application in various professional roles. The second half is interview preparation, through which you will be prepared for the toughest interviews in the tech world today.

How is generative AI relevant to my role?

Many companies have started adding Generative AI skills to job descriptions of several tech roles including Software Engineering, Engineering Managers, Product Managers, and Technical Program Managers. We analyzed over 10,000 JDs and found that over 10% of the roles now require GenAI skills. You need to know not just how to use various GenAI tools such as GPT and Midjourney, but also how to best leverage the power of GenAI to increase productivity, efficiency, and creativity.

What are the prerequisites for the EdgeUp Program?

This program is suitable for anyone in the tech field with a strong inclination to learn Generative AI, and land their dream roles at top-tier tech companies.

How do I enroll in the program?

The best way to join the course is to first register for our pre-enrolment session here. You will learn all about the course, its cost, and other useful details.

Are the modules self-paced or live?

Applied GenAI modules are all live, and the domain-level classes could be either self-paced or live. You will also receive class recordings after each day’s session.

How much time would I need to put in each week for the EdgeUp programs?

You will need to put in around 8 to 12 hours each week for this course.

Will I have access to the learning modules after I complete the program?

Yes. You will be able to access all class recordings even after you complete the program.

Learn Generative AI and Transition to Tier-1 Companies

Next webinar starts in

Tools you’ll learn

Interview Kickstart EdgeUp—Gain the AI Edge & Boost Your Career

Back-end Engineers

4.5

Front-end Engineers

4.6

Full-stack Engineers

4.7

Test Engineers

4.8

Product Managers

4.8

Engineering Managers

4.7

Technical Program Managers

4.7

Machine Learning Engineers

4.6

Data Scientists

4.6

Why EdgeUp?

GenAI-enabled Job Descriptions & skills

Detailed Curriculum

Back-end Engineers

Front-end Engineers

Full-stack Engineers

Test Engineers

Product Managers

Engineering Managers

Technical Program Managers

Machine Learning Engineers

Data Scientists

Other Tech Professionals

Capstone Projects

General Tech Projects

Software Engineering Projects

Product Management Projects

Technical Program Management Projects

Engineering Management Projects

General Tech Projects

+ Instructors to Train You in Live Classes

Randy Cogill

Jay Pillai

FAANG+ Leader

Shruti Goli

Ahsan Ali

The IK Experience: What Our Alumni Are Saying

Mike Kane

Davide Testuggine

Get upto 15 mock interviews with hiring manager

Hiring managers from Tier-1 companies like Google & Apple

Domain-specific Interviews

Detailed personalized feedback

Transparent, non-anonymous interviews

1. Flexible schedule

4. Technical and behavioral interviews

2. Remote interview experience

5. Level-specific interviews

3. Feedback documentation

6. Interviewer of your choice

How to Enroll for Interview Kickstart’s EdgeUp Program

Next webinar starts in

Technical Interview prep program

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