Machine Learning Bootcamp

Become an ML Engineer in 4 Months!

  • Online
  • 4 Months
  • 16th January

About this Program

This is a 4-month Bootcamp to enable participants to learn relevant Machine Learning skills and launch their careers in the field. The program is meant for those who are aiming to transform their careers and become ML Engineers as well as those who want to incorporate Machine Learning training into their current jobs/careers to remain competitive. 
The defining characteristic of this program is that it goes beyond training and imparting key skills. It will also enable you to communicate effectively, think critically, and problem solve. Exclusive mentorship and career guidance will be provided to participants. 
The Graduates of the Bootcamp will not have just learnt tools and methods but will have become ML Engineers – competent, confident, and ready to work. We look forward to working with you over the next 4 months as we master Machine Learning and the ways it is revolutionizing the future of work.

Key Features

Focused Learning Path

Expert Instructors

Hands-on Experiential Learning

Help and Support from Teaching Assistants

Networking and Social Connections

LinkedIn Coaching & Resume Building

Interview Preparation

Industry Ready Portfolio

1-on-1 Coaching and Mentorship

Job Search Guidance and Support



Learning Outcomes

This is an accelerated preparatory week to ensure that essential concepts are revised. It will be fast-paced and will go over everything that is required to begin an in-depth study of Machine Learning.

Statistical Foundations

Mathematical Foundations

Microsoft Excel

Python Revision


Learning Outcomes

  1. Get acquainted with the meaning of Machine Learning along with relevant case studies
  2. Delve into Feature Engineering
  3. Get familiar with Statistical Models and Tree Based Models
  4. Create your first professional portfolio project

Introduction to ML
• What is ML? (Demystifying the buzz words such as ML, AI, DS and DL)
• Building Blocks for ML & Real World Examples
• Exploratory Data Analysis

Feature Engineering
• Data Scaling
• Identifying important features
• Creating new features

Statistical Models, Tree Based Models
• Bayes’ Theorem
• Naive Bayes
• Decision Tree

Portfolio Building
• Portfolio Project 1


Learning Outcomes

  1. Learn how to deal with Regression Models
  2. Learn about Neural Networks
  3. Create your second professional portfolio project
  4. Get an insight into Unsupervised Learning

Regression Models
• Linear Regression
• Logistic Regression

Neural Network:
• Perceptron
• Artificial Neural Networks
• Intro to Deep Neural Nets

Portfolio Building
• Portfolio Project 2

Unsupervised Learning
• K-Means Clustering
• Hierarchical clustering
• Principal Component Analysis


Learning Outcomes

  1. Gain familiarity with major NLP concepts.
  2. Create your third professional portfolio project.
  3. Learn Computer Vision.
  4. Revise and Consolidate Concepts and Projects.

• Basic Text Processing
• NLTK & SpaCy
• Intro to Transformers

Portfolio Building
• Project Portfolio 3

Computer Vision
• Basic Image Processing
• CNN and its advanced variants

• Review Concepts & Projects

Career Counseling & Job Market Preparation



Learning Outcomes

  1. Develop your personal brand and revamp your LinkedIn profile and resume.
  2. Learn about online and offline networking strategies and how to navigate networking events with confidence.
  3. Learn unconventional methods of job hunting.
  4. Learn effective interview strategies and how to answer behavioral as well as domain related questions.

LinkedIn and Resumes

Networking and Mock Networking Event

Job Hunting

Interview Workshops and Mock Interviews

Career services that will get you hired

1-on-1 consultative sessions with instructors and mentors.

Regular speaker series with industry professionals and hiring managers.

Community building with a network of Machine Learning professionals

LinkedIn coaching and resume building.

Strategies for unconventional methods of job hunting.

Interview workshops and mock interviews.


Meet our experienced Machine Learning instructors. Our curriculum is created and taught by Machine Learning Experts with years of real-world industry experience.

Usman’s core specialties include Advanced Analytics, Machine & Deep Learning, and Optimization. He has worked in various industries including financial, retail, FMCG, consumer electronics and telecommunications in Australia. Currently, he is leading the data science team in nbn Australia , a leading broadband company in the country. He is also pursuing his PhD in Machine Learning.

I'm the CFO!!!

Hussain has delivered data science solutions to global clients including Barclays, OCBC, KPMG, Royal Fidelity, and multiple Government as well as Intelligence organizations. He has taught Machine Learning and Deep Learning at SZABIST.


To enroll in the Machine Learning Bootcamp, you must meet the following criteria: 

Have basic data literacy and be aware of data types and the data life cycle

Demonstrate familiarity with fundamental and descriptive statistics

Have an understanding of probability and linear algebra

Be able to carry out data cleaning and analysis on Microsoft Excel, and work with Pivot Tables

Have an intermediate level proficiency in Python

Admission Process

Call for Applications

24th November, 2022

Shortlisting of Candidates

31st December, 2022


5th-6th January, 2023


8th-11th January, 2023

Finalization of cohort

14th January, 2023

Commencement of Bootcamp

16th January, 2023

Pricing Plans

Standard Monthly Plan

PKR 20,000 per month
  • Standard Monthly Program

Monthly Plan for atomcamp alumni & women

PKR 15,000 per month
  • Monthly Plan for atomcamp alumni & women

Lumpsum Payment (Advance Payment)

PKR 50,000
  • For 4 Months

Frequently Asked Questions

Are the live sessions recorded for viewing later?

Yes, all sessions are recorded and will be available for the participants to view at a later date.

Are there any discounts available?

Yes, if you are from a disadvantaged background, have taken a course with atomcamp previously, or are a woman, you may be eligible for a 25% scholarship/financial aid. Please contact for further details relevant to your profile.

What background is needed to join this Bootcamp?

If you want to join this Machine Learning Bootcamp, please refer to the eligibility requirements given above before applying. If you need further support in making a decision with regards to joining the Bootcamp, please reach out to or to set up a meeting.

Will a certificate be awarded for completion of this Bootcamp?

Yes, you will be awarded a certificate if you have 80% attendance and have completed all assignments and projects to the satisfaction of the instructors.

How many hours per week is the required commitment for this Bootcamp?

The total class hours are 6 per week. Aside from that, you will be assigned 6 hours’ worth of homework. Only commit to the Bootcamp if you are willing to put in this much effort.