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Placement Support

AI ML Interview Preparation Program

BECOME AN AI/ML EXPERT WITH OUR

AI ML Interview Preparation Program

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Learn directly from MAANG+ Hiring Managers, Tech Lead, Experts

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17 Weeks of Live Interview Preparation

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Cheat Sheets, Question Banks, Code Templates and More

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1000+

Hired By Top Tier Companies

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40 to 60%

Average Salary Hike

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$350k

Highest Salary

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99.6%

NPS Score

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4.8/5

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4.8/5

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INTERVIEW PREPARATION PROGRAM HIGHLIGHTS
Standout Features of AIML Course!
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17 Weeks of Interview Prep

Structured, outcome-driven prep covering coding, ML, design, and soft skills like real interviews.

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Taught by MAANG+ Experts

 Learn directly from MAANG+ professionals with decades of AI/ML industry experience.

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20 Mock Interviews

20 real interview simulations with feedback and mentorship from MAANG+ experts.

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Interview-Ready ML Toolkit

Includes cheat sheets, code templates, question banks, and STAR frameworks.

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Hands-On Learning Approach

Build job-ready skills from day one through real-world projects and practical exercises.

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Trial Week Access

First experience the course—continue only if it’s right for you.

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Extended Support Period

6 months of post-class guidance, mock interviews, doubt clearing, and advice.

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Unlimited Doubt-Clearing

Personalized help anytime—technical or strategic career guidance, no session limits.

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Lifetime LMS Access

Unlimited access to recordings, resources, and materials for future review.

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Extended Support Period

6 months of post-class support for revisions, mock interviews, doubts, and career guidance.

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Placement Support

Personalized AI/ML branding with resume help, LinkedIn optimization, and career coaching.

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100% Money-Back Guarantee

If it doesn’t meet your expectations, get your money back. 

INTERVIEW PREPARATION COURSE REVIEWS

Testimonials

All Reviews

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Google

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Trustpilot

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This Program Helped Me Get the Job—No Fluff

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I’d tried a bunch of courses before, but none came close to this one. I wasn’t e...Read More

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Daniel Foster

Software Engineer

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Real-World Prep That Actually Works

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I was looking to move into a more technical role, and this course was exactly wh...Read More

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Lily Morgan

Business Intelligence Analyst

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Went From Nervous to Confident—and Got the Job

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I used to panic at the thought of technical interviews, especially anything ML-r...Read More

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Ryan Mitchell

Junior Developer

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The Best Career Move I’ve Made

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Switching into AI felt overwhelming at first, but this course made it doable. Th...Read More

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Megan Price

QA Specialist

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I Got the Offer—Thanks to This Course

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I’d been stuck in the same role for years, trying to break into ML. This program...Read More

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Jason Clark

Backend Developer

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Yellow Star4.9/5
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Yellow Star4.7/5
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Yellow Star4.6/5
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Yellow Star4.5/5

INTERVIEW PREPARATION PROGRAM TIMINGS

Class Timings

  • Sunday – 9 AM PST to 1 PM PST  
  • Thursday – 6 PM PST to 8 PM PST  
  • Tuesday – 6 PM PST to 8 PM PST (for doubt clearing)
  • Post Program completion – 6 Months of support period will be provided where candidates can go through doubt clearing sessions and take mock interviews. 
     

INTERVIEW PREPARATION PROGRAM

WHAT YOU WILL LEARN

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Programming Languages

Master Python 3 for ML, scripting, and data tasks, using Jupyter, Colab, VS Code, and terminal.

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Data Handling & Processing

Clean, transform, and analyze data efficiently with Pandas, NumPy, and TimeSeriesGenerator for deep learning prep.

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Visualization & EDA

Create insightful plots with Matplotlib, Seaborn, and Plotly to explore and visualize your data effectively.

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Statistics & Scientific Computing

Apply statistical tests and optimizations using SciPy, and perform in-depth modeling with StatsModels as needed.

INTERVIEW PREP PROGRAM ELIGIBILTY

Prerequisites

  • Current ML Engineers
  • Current Data Scientists working with MLOps 
  • Fresh Graduates with ML Major degrees or PhD degrees  
     

WHO CAN ATTEND THE AI/ML INTERVIEW PREP TRAINING

Who This Course Is For

  • Data Scientists Working in ML Ops

  • Machine Learning Engineers

  • ML Ops Engineers

  • AI Engineers

INTERVIEW PREPARATION PROGRAM

Curriculum

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Module 1: Data Structures & Algorithms (DSA) (5 Weeks)

Learning Objectives: 


Build deep DSA skills and system design thinking to solve coding challenges and architect scalable systems for real-world interview scenarios.

Week 1: Sorting & Algorithm Foundations Topics Covered: 

  • Introduction to sorting algorithms 
  • Basics of asymptotic analysis (Big O, Theta, Omega) 
  • Worst-case and average-case time complexity 
  • Sorting algorithms: Bubble, Selection, Insertion, Merge, Quick, Heap 
  • Algorithm paradigms: Divide & Conquer, Decrease & Conquer 
  • Presorting and its applications 
  • Merge sort on linked lists, 3-way quicksort 


Week 2: Recursion & Backtracking Topics Covered: 

  • Recursion basics: base case, recursive case 
  • Recursive mathematical problems (factorial, Fibonacci) 
  • Combinatorial enumeration (nCr, permutations) 
  • Exhaustive enumeration with backtracking 
  • Letter case permutations, combinations, subsets 
  • Sudoku solver, N-Queens, Rat in a Maze 


Week 3: Trees & Hashing Topics Covered: 

  • Binary Search Trees (BST): insert, search, min/max 
  • Dictionaries & hash tables: collision resolution, load factor 
  • Tree traversals: Inorder, Preorder, Postorder 
  • Level order traversal (BFS), DFS on trees
  • BST problems: Diameter, Count Univalue Subtrees, Lowest Common Ancestor 
  • Tree construction from traversal arrays 


Week 4: Graphs & Connectivity Topics Covered: 

  • Graph types: directed, undirected, weighted 
  • Representation: adjacency list, matrix, edge list 
  • BFS and DFS traversal 
  • 7 Bridges of Königsberg and Eulerian paths 
  • Stack-based DFS and recursion-based DFS 
  • Finding connected components 
  • Graph problems: bipartite check, cycle detection, topological sort 


Week 5: Dynamic Programming (DP) Topics Covered: 

  • Principles of DP: overlapping subproblems, optimal substructure 
  • Top-down (memoization) vs bottom-up (tabulation) 
  • Classic problems: Climbing Stairs, Subsets of size k 
  • DP on grids: Unique paths, obstacles, path sums 
  • Coin Change, Edit Distance, Word Break, Equal Subset Partition  
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Module 2: System Design (3 Weeks)

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Module 3: AI/ML Interview Preparation Plan (7 Weeks)

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Module 4 : Soft Skills & Behavioral (2 Weeks)

AI ML INTERVIEW PREP FAQs

Frequently Asked Questions

Machine Learning Interview rounds

Sample Interview Questions

Career Path & Salaries

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What is the Interview Process Like for Machine Learning Roles at MAANG+ and Tier-1 Companies?

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The Machine Learning interview process at top tech companies generally includes multiple stages designed to assess your technical, analytical, and behavioral fit. Here's a breakdown of what to expect: 

Initial Technical Screening 

1.Format: Phone or virtual interview 
2.Focus Areas: 

  • Basic understanding of Machine Learning concepts 
  • Discussion of past ML projects 
  • Coding problems (often LeetCode medium to hard level) 


3. Core Technical Rounds (On-site or Virtual – 3 to 8 Rounds) 

a. Coding Rounds (1–2 rounds) 

  • Data Structures and Algorithms 
  • ML-specific coding tasks 
  • In-depth ML project discussions 


b. System Design Rounds (1–2 rounds) 

  • Scalable software system design 
  • ML system design (e.g., building a recommendation engine) 
  • Note: For candidates with <3 years of experience, ML system design may be replaced with an additional ML fundamental round. 


c. ML Technical Rounds (1–3 rounds) 


1.Breadth and depth of ML understanding 
2.Topics include: 

  • Linear/Logistic Regression 
  • Decision Trees, SVM, Neural Networks 
  • Optimization techniques (e.g., Gradient Descent) 
  • Loss functions (e.g., Cross-Entropy Loss) 
  • Tools and deployment pipelines 



3. Behavioral Round 

  • Experience and project-based discussion 
  • Open-ended questions to assess cultural and team fit 


Summary 


Candidates should prepare for: 

  • Strong coding and DSA skills 
  • A solid grasp of ML algorithms and system-level thinking 
  • The ability to explain and discuss past ML projects 
  • Clear communication and alignment with company values during behavioral interviews