Techademy AI ML Interview Preparation Program

Placement Support

AI ML Interview Preparation Program

BECOME AN AI/ML EXPERT WITH OUR

AI ML Interview Preparation Program

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

17 Weeks of Live Interview Preparation

Cheat Sheets, Question Banks, Code Templates and More

Can’t wait?

Book a session with your Learning Advisor

1000+

Hired By Top Tier Companies

40 to 60%

Average Salary Hike

$350k

Highest Salary

99.6%

NPS Score

4.8/5

INTERVIEW PREPARATION PROGRAM HIGHLIGHTS

Standout Features of AIML Course!

17 Weeks of Interview Prep

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

Taught by MAANG+ Experts

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

20 Mock Interviews

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

Interview-Ready ML Toolkit

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

Hands-On Learning Approach

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

Trial Week Access

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

Extended Support Period

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

Unlimited Doubt-Clearing

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

Lifetime LMS Access

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

Extended Support Period

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

Placement Support

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

100% Money-Back Guarantee

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

INTERVIEW PREPARATION COURSE REVIEWS

Testimonials

All Reviews

Google

Trustpilot

This Program Helped Me Get the Job—No Fluff

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

Daniel Foster

Software Engineer

Real-World Prep That Actually Works

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

Lily Morgan

Business Intelligence Analyst

Went From Nervous to Confident—and Got the Job

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

Ryan Mitchell

Junior Developer

The Best Career Move I’ve Made

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

Megan Price

QA Specialist

I Got the Offer—Thanks to This Course

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

Jason Clark

Backend Developer

4.9/5

4.7/5

4.6/5

4.5/5

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

Programming Languages

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

Data Handling & Processing

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

Visualization & EDA

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

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

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

Module 2: System Design (3 Weeks)

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

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

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

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