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Machine Learning Crash Course

Uplevel in your career and land your dream job with this course designed and taught by FAANG+ AI/ML Engineers

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Tools you’ll learn

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Detailed Curriculum

Programming with Python
Introduction to Machine Learning
Classical Machine Learning
Introduction to Deep Learning
Applied Generative AI
LLMs and Capstone Project
Interview Prep

Programming with Python

  • Introduction to Programming with Python
  • Introduction to Programming with Python
  • Month 1

Introduction to Machine Learning

  • Data Analysis
  • ML Fundamentals
  • Fundamentals of Generative AI + Prompt Engineering
  • Build your first ML Model
  • Month 2

Classical Machine Learning

  • Tree Based Models
  • Model Evaluation & Interpretation
  • Unsupervised Learning
  • Ensemble Methods
  • Month 3

Introduction to Deep Learning

  • Model Optimisation Techniques
  • Neural Networks Basics
  • ML Architectures
  • Case Studies
  • Month 4

Applied Generative AI

  • Transformer Based Models
  • App Building with ML and GenAI
  • Case Studies
  • Month 5

LLMs and Capstone Project

  • Deep-Dive into LLMs
  • GenAI in Action
  • Examples of some projects:
    1. Smart Retail Analytics: Customer Segmentation and Personalized Recommendations
    2. Automated News Analysis and Content Generation
    3. Conversational AI for Customer Support with LangChain and RAG
  • Month 6

Interview Prep

  • DSA & Algorithms
  • System Design
  • Machine Learning Masterclass
  • Mock interviews
  • Interview strategy and success
  • Offers and negotiation
  • Month 7

The curriculum is constantly being updated as per industry developments and is subject to change.

Add-on Specializations

You can add any of the below-advanced learning modules to your course to dive deeper into ML/Data Science and increase your chances of landing a lucrative job role.

Advanced Natural Language Processing

Advanced Computer Vision

Data Visualization & Storytelling

Big Data with Apache Spark

Capstone Projects

ReviewSum AI – Review Analysis Tool

  • Elevate business insights with ReviewSum AI, a tool inspired by Amazon’s advanced review summarization capabilities. Utilize NLP, including Generative AI and LLMs, to transform voluminous Amazon reviews into concise, insightful summaries. This automated tool helps businesses enhance product perception, offer proactive customer service, and conduct effective market research. It turns lengthy customer feedback into actionable data, unlocking new growth and success opportunities.

Playlist Pulse – Music Recommendation System

  • Develop Playlist Pulse, a sophisticated project using advanced ML/DL algorithms to classify music tracks by mood and genre, akin to Spotify’s music recommendation engine. This system recommends subsequent tracks and leverages Power BI to create an interactive dashboard that collects and analyzes user feedback, offering detailed insights into music preferences.

Capstone Projects are subject to change as per industry inputs.

Why Choose Interview Kickstart Machine Learning Course

Taught by FAANG+ ML Engineers

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

Learn Machine Learning and GenAI

Learn the basics of ML, practical GenAI, and their application in real-world use cases

Practical Learning with Capstone Projects

Real-world machine learning projects that simulate AI/ML challenges

Interview Prep Modules

Customize your learning with advanced specializations in critical areas, positioning you for specialized roles in the industry

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

Who Is Eligible for This Course?

Junior-to-senior software professionals looking to switch careers to AI/ML

  • Front-end, Back-end, Full-stack, and other Software Engineers
  • Software Tech Lead
  • Test Automation Engineers
  • Security Software Engineer
  • SAP & .Net developers
  • Mobile Developer (iOS/Android), Web Developer, Game Developer

Junior-to-senior Tech Managers without experience in coding but looking to learn ML

  • Tech Product Managers
  • Engineering Managers
  • Tech Program Managers

Junior-to-mid level Semi/Tech Professionals

  • Cyber Security Engineers, Security Analysts, Network Engineers
  • Software Quality Engineers/Analysts
  • Embedded Software Engineers, IoT Engineers, Firmware Engineers
  • Database Administrators, VBA Developers, BI Developers
  • Data Analyst, Business Analyst
  • Cloud Engineers, Cloud Architects
  • Mechanical Engineers, Electrical Engineers
  • DevOps, Site Reliability Engineers

Junior professionals from non-STEM/non-coding backgrounds with a high interest in learning ML

  • SAP Consultants, Tech-consultants
  • Non-Tech Program and Product Managers
  • Healthcare/Medical Informatics Analyst, Biostatistician
  • Risk Management Specialists - Insurance
  • IT professionals

falag + Instructors to Train You in Live Classes

Ashish Kaila

Enthusiast & Staff Software Engineering

FAANG+ Leader

Randy Cogill

Senior Research Scientist
instructor

Jay Pillai

Engineering Leader - GenAI

FAANG+ Leader

Shruti Goli

Senior Product Manager, Incode

Ahsan Ali

Applied Scientist
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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.

How to Enroll for Interview Kickstart’s Machine Learning Crash Course?

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

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Learn more about the course & pricing
It's Free

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FAQ

Interview Kickstart’s ML Program will equip you with ML skills and prepare you for interviews at top tech companies. You will not only learn the essentials of classical ML, Generative AI, and LLMs but also be ready to ace interviews to land your dream ML job.
Yes, this course is fully aligned with the demands of the market. It is designed and taught by ML Engineers and Data Scientists who are active practitioners of the technology in FAANG+ companies. These are the folks who are at the forefront of innovation and cutting-edge AI/ML tech today, which means you get to learn from the best and learn the latest in AI/ML today.
In our course, you will spend 6 months learning Python, ML, Neural Networks, Generative AI, and LLMs, and the next 2 months preparing for Machine Learning interviews.
Yes. After learning ML, Neural Networks, GenAI, and LLMs for six months, you will spend two months on rigorous and comprehensive interview preparation. This will prepare you for the toughest ML interviews in the tech world today.
With our Machine Learning Crash Course, you will gain a solid foundation in ML, Generative AI, and Large Language Models (LLMs), preparing you for roles such as ML Engineer, Data Scientist, AI Engineer, Data Analyst, or Business Analyst.
There are no prerequisites for the program. It is ideal for junior-to-mid-level tech professionals with experience in coding and looking to switch careers, junior-to-senior-level tech managers without experience in coding and looking to learn ML, and junior-level professionals from non-STEM/coding backgrounds with a high interest in learning ML. This program is not a good fit for non-technical individuals with more than 7 years of experience outside of tech.
Classical ML includes Regression, Classification and Clustering, and Bagging and Boosting. The ML program covers all these topics well, including theoretical intuition, mathematical foundations, practical use cases, implementation, and real-world applications via case studies and projects.
Applied Generative AI is one of the central themes of Interview Kickstart’s Machine Learning Program, which includes comprehensive Generative AI courses. The course enables students to use GenAI in their day-to-day work to solve complex problems efficiently. It covers the internal deep learning behind Generative AI, building LLM applications, and using platforms and frameworks such as OpenAI, Hugging Face, and LangChain.
The program covers essential deep learning frameworks and architectures like Neural Networks, GANs & VAEs, Transformers & BERT. These will set a strong foundation for deep learning concepts such as natural language processing and Generative AI in a hands-on setting.
There are 3 key differences between Interview Kickstart’s ML Course and Advanced ML Course: ‍ • Curriculum:  The ML Course covers the essentials of Machine Learning and provides a specialization option, whereas the Advanced ML Course dives deep into all aspects of Machine Learning Engineering. ‍ • Duration: The ML Course is an 8-month program, where the first 6 months are spent learning ML and GenAI and the next 2 months on interview prep. The Advanced ML Course is a 14-month program, where the first 12 months are spent learning ML and GenAI and the next 2 months on interview prep. ‍ • Outcomes: The ML Course is meant to give you a robust working knowledge of ML, GenAI, and LLMs, and you can start your career as an ML Engineer, Data Scientist, AI Engineer, Data Analyst, or Business Analyst. The Advanced ML Course is in-depth and is meant to make you a Deep Learning Engineer, ML Engineer (specialized roles), or Applied Scientist.
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.
The learning modules in the ML Course are a mix of self-paced pre-class videos and live classes. You will also receive recordings after each session.
You will need to put in around 12 to 16 hours each week for this course. Machine Learning is a specialized topic, yet it is very interesting as it allows you to drive very useful insights and inferences from data. So, all your efforts and hard work will pay off at the end of the program.
Yes. You will be able to access all class recordings even after you complete the program.
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