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How to Nail your next Technical Interview

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You may be missing out on a 66.5% salary hike*

Nick Camilleri

Head of Career Skills Development & Coaching
*Based on past data of successful IK students
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FREE course on 'Sorting Algorithms' by Omkar Deshpande (Stanford PhD, Head of Curriculum, IK)

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Scale Your AI Systems with Advanced MLOps Training

Efficiently deploy and maintain complex, large-scale ML models.

  • Master the entire MLOps Lifecycle
  • Learn from FAANG+ AI/ML Engineers
  • Understand AWS and learn to work with EC2 and S3
This program is for Machine Learning Engineers/Applied Scientists/Data Scientists
Register for Pre-enrolment Webinar
Learn more about the course & pricing
It's Free

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Cutting-edge tools & technology stack

Whether it’s for model design, deployment, monitoring, or security, you will use a range of in-demand tools, libraries, languages, and technologies during this program.

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Why Choose This MLOps Course?

Comprehensive Curriculum

End-to-end MLOps Lifecycle Mastery

Learn how to efficiently deploy and maintain scalable ML model.
Rigorous Mock Interviews

Expert-Led Curriculum

360° MLOps course designed and taught by FAANG+ experts to help you effectively deploy ML models
Plenty of 1 x 1 Help

Hands-on Expertise

Move beyond theory with practical skills in designing, implementing, and putting models to production with AWS.
Career Skills Development

Stay Current, Stay Relevant

 The field of ML and AI moves fast. Our course, grounded in the latest research and industry demands, keeps you at the forefront.
Salary Negotiation

Mock interviews with FAANG+ Data Scientists

Get ahead of the competition - showcase your expertise with a comprehensive portfolio of high-end in-demand projects.
Salary Negotiation

Live, Interactive Expert Sessions

Engage with AI pioneers and draw insights from their vast experience.

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Course Highlights
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360’ interview preparation
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Build successful interview strategies and practice answering the toughest security engineering interview questions
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Extensive coverage of interview relevant Security Engineering topics such as Applied Cryptography, Application, Network and Cloud Security and more  
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Get mentored by our highly experienced instructors working as active hiring managers and at FAANG+ companies and know exactly what it takes to ace tech and managerial interviews.

Course Highlights

(Program duration: 9 weeks)
Comprehensive Curriculum

Advanced Data Handling Techniques

Learn sophisticated methods for data storage, versioning, and utilization of feature stores.
Rigorous Mock Interviews

Practical Skills in Model Training and Deployment:

Develop expertise in hyperparameter tuning, model packaging, containerization, and deployment using modern CI/CD practices.
Plenty of 1 x 1 Help

Kubernetes and Cloud Platforms Utilization

Gain hands-on experience in using Kubernetes for orchestrating containers and leveraging cloud platforms for scalable ML solutions.
Career Skills Development

Monitoring, Security, and Governance in ML

Acquire skills in monitoring ML models, managing data drift, and ensuring robust security and governance practices in ML pipelines.
Eligibility Criteria
This program is best suited for Machine Learning Engineers, Applied Scientists, and Data Scientists looking to revisit or master MLOps skills for pushing large-scale ML models to production.

Prerequisites

Comprehensive Curriculum
Knowledge of Python or any other scripting language.
Rigorous Mock Interviews
Prior experience in basic or classical ML modeling/prototyping
Plenty of 1 x 1 Help
Comfortable with data processing and deep learning concepts.

Train with MLOps Industry Practitioners

Our highly experienced instructors are active ML Professionals at FAANG+ companies, bringing a treasure trove of knowledge and industry expertise.
instructor

Jude Safo

Former ML Engineer
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instructor

Naveen Neppalli

Former Head of Engineering & Machine learning
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instructor

Parivesh Priye

Applied Scientist
FAANG+ Leader
instructor

James Vance

Machine Learning Engineer
FAANG+ Leader
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Career Impact: 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.
siva karthik gade

Siva Karthik Gade

Machine Learning Engineer
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 coaches. IK brings together people with the same ambition on their platform, Uplevel, to guide and inspire each other.
humberto Gonzales Granda

Humberto Gonzales Granda

Machine Learning Engineer
Placed at:
Interview Kickstart's dedicated team of instructors and coaches provided exceptional support and mentorship. Their extensive knowledge and experience in the tech industry is evident in the program's meticulously crafted curriculum. The diverse range of topics covered, including data structures, algorithms, and systems design, was nothing short of impressive, ensuring that I was well-equipped to tackle any challenge that came my way. One standout feature that sets Interview Kickstart apart is the personalized attention provided to each participant. The program's well-structured curriculum, passionate instructors, and unparalleled support make it a game-changer that can unlock your true potential.
Mike Kane

Mike Kane

Lead Data Engineer
Placed at:
For many working professionals, going through examples and different perspectives are very valuable…. Interview Kickstart was great because its structure helped me understand each problem in my interview. The high sense of comradery in Discord was also great! I had a study group with other people in my cohort and felt the engagement was much stronger than in an academic setting.
Davide Testuggine

Davide Testuggine

Software Engineer
Placed at:
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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.
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Students who chose to uplevel with IK got placed at

engineering
Siva Karthik Gade
SDE, Machine Learning
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engineering
Sai Marapa Reddy
SWE, Machine Learning
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enginnering
Safir Merchant
SWE, Machine Learning
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Jameson Merkow
Principal AI Engineer
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Sayan Banerjee
Data Scientist II
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Manika Kapoor
Senior Deep Learning Scientist
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Mike Kane
Lead Data Engineer, Analytics
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Akshay Lodha
Data Engineering & Analytics
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Anju Mercian
Data Engineering Consultant
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Alokkumar Roy
Data Engineer
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13,500+
Tech professionals trained
$1.267M
Highest offer received by an IK alum
53%
Average salary hike received by alums

MLOps Detailed Curriculum

Design Considerations
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1 week
1

Fundamental concepts of MLOps

2

Introduction to AWS and tools such as Airflow

3

Learn to work with EC2 and S3

4

Monitoring and Iterative Improvement

5

Security and Governance

6

Tools/ Language Used: Python, Google Colab, Numpy, Pandas, Scikit-Learn, Keras, PyTorch, and Cloud Platforms (AWS)

Data Management
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1 week
1

Data Storage Patterns - LFS, NFS, Cloud, Databases

2

Data Lakes and Feature Stores

3

Data Versioning and Tracking

4

Feature Stores

5

Data Pipelining

6

Tools/ Language Used: Git, Data Version Control (DVC), Git LFS, Feast, Airflow

Model Training -1
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1 week
1

Large Scale/Distributed Hyperparameter Tuning and

2

Experiment Tracking

3

 Tools/ Language Used: skopt, Raytune, MLflow Tracking

Model Training -2
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1 week
1

Project Packaging and Model Versioning

2

Distributed Training

3

Tools/ Language Used: MLflow Model Registry, TensorFlow Distributed, Distributed Data-Parallel and FSDP

Model Deployment and Inference - 1
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1 week
1

Containerization with Docker

2

CI/CD

3

Model Deployment Considerations

4

Model Preparation for Deployment

5

Batch Inference/Deployment

6

RESTful APIs based Real Time Inference/Deployment

7

Tools/ Language Used: Pickle, Tensorflow, Pytorch, Airflow, FastAPI, Swagger

Model Deployment and Inference - 2
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1 week
1

Model Containerization

2

Serving Frameworks

3

Scale Inference on Cloud

4

Model Preparation for Deployment

5

ML Continuous Integration/Deployment

6

Tools/ Language Used: Docker, Tensorflow Serving, Pytorch Serving, MLFlow Serving, AWS EC2, AWS Lambda, MLflow Registry, Jenkins

MLOps - Kubernetes Architecture
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1 week
1

Containers and Orchestration

2

Kubernetes Architecture

3

Kubernetes Deployments

4

Kubernetes Services

5

Scaling and Updates

6

Tools/ Language Used: Kubernetes

Monitoring & Continuous Training
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1 week
1

Data and Concept Drift

2

Performance Benchmarking

3

Realtime Model Monitoring

4

Drift Detection

5

Model Latency

6

Performance Visualization

7

Iterative Learning Reasons

8

HITL

9

Active Learning

10

Iterative Training Pipelines

11

A/B Testing

12

Tools/ Language Used: MLflow, Grafana, Prometheus

Security and Governance
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1 week
1

Key Concepts in Data Security: CIA Triad, Access Control, Encryption and Masking

2

Differential Privacy

3

Federated Learning

4

Data Governance Principles: Ownership, Stewardship, Classification, Retention

5

Compliance Frameworks: GDPR, CCPA, HIPPA, etc.

6

Securing ML Pipeline Components - Data Storage, Models and APIs

7

Tools/ Language Used: Apache Ranger, Apache Atlas, Faker, Data Encryption Libraries, Tensorflow Federated, Tensorflow Privacy

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A typical week at Interview Kickstart

This is how we make your journey structured and organized. Our learners spend 10-12 hours each week on this course.

Sun

Attend online live sessions
Attend 4-5 hour live sessions covering concepts & applications of module concepts
Each class covers a wide variety of approaches, fully hands-on with problems and frameworks to solve them to reflect latest advancements in the field
Live feedback from a Tier-1 tech instructor

Mon-Wed

Practice problems & case studies
Practice the concepts taught in live sessions to solve assignment questions
Live doubt-solving from FAANG+ instructors

Thu

1:1 access to instructors
2 hour review session covering assignment solution walkthrough on the current week's topics and other best practices

Every day

1:1 access to instructors
Personalized coaching from FAANG+ Instructors
Individualized and detailed attention to your questions
Contact for Pricing
Already preparing or want a sneak peek? Try the FE Interview Prep 7-day email course

How to Enroll for the Advanced MLOps Program

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

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enroll course

FAQs on Advanced MLOps Training Program

1
What is the application of MLOps in different industries?
2
Why should I take the Advanced MLOps Program?
3
Is the MLOps Program self-paced or live?
4
Is the MLOps program virtual or are there in-person classes?
5
How much time would I need to put in each week for this MLOps program?
6
What are the prerequisites for this MLOps Program?
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What is MLOps and how is it applied in different sectors?
8
Will the Advanced MLOps Training Program help me get better jobs?
9
Will I have access to the modules in Advanced MLOps after I complete the program?
10
What kinds of projects will I work on in this program?
11
Does this program reflect the latest technology developments in MLOps?
12
Will I have to spend extra on anything while doing this program?
Already preparing or want a sneak peek? Try the FE Interview Prep 7-day email course
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