Data Science Bootcamp

Become a Data Scientist in 6 Months!

  • Online
  • 6 Months

About this Program

This is a 6-month Bootcamp to enable participants to learn relevant data skills and launch their careers in the field. The program is meant for those who are aiming to switch into a data science career as well as those who want to incorporate data science 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 data scientists – competent, confident, and ready to work. We look forward to working with you over the next 6 months as we master data science and the ways it is revolutionizing the future of work.


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Key Features

Focused Learning Paths

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


MONTH 1: Data Literacy & Excel Foundation

Learning Outcomes

1. Become familiar with and demonstrate clarity in understanding of basic data and statistical concepts.
2. Enhance understanding of mathematical foundations and operations for data science.
3. Become proficient in data cleaning, data processing, and data management with Microsoft Excel. 
4. Become acquainted with Tableau for data visualization

Data Literacy
• Data Types
• Data Life Cycle

• Data Cleaning
• Data Preparation

Excel Advanced
• Pivot Tables
• Basic Analysis

Data Analytics and Visualization on Tableau

MONTH 2: SQL Foundation

Learning Outcomes

  1. Identify a subset of data from a column or set of columns and write an SQL query to limit to those results.
  2. Use SQL commands to filter, sort, and summarize data.
  3. Create an analysis table from multiple queries using the UNION operator.
  4. Manipulate strings, dates, and numeric data using functions to integrate data from different sources into fields with the correct format for analysis.

Selecting and Retrieving Data with SQL

• Statistical Foundation

Subqueries and Joins in SQL

• Statistical Foundation

Filtering, Sorting, and Calculating Data with SQL

• Mathematical Foundation

Modifying and Analyzing Data with SQL

• Mathematical Foundation

MONTH 3: Python

Learning Outcomes

  1. Get familiar with basic Python syntax, data types, operators, and expressions.
  2. Learn about for and while loops, break and continue statements, and functions. 
  3. Learn to work with Numpy and Matplotlib
  4. Learn about handling exceptions, raising exceptions, and custom exceptions. 

Introduction to Python
• Setting up a development environment
• Basic Python syntax and data types
Basic Operators and Expressions
• Basic operators and expressions
• Control structures: if else case statements

• For and while loops
• Break and continue statements
• Defining and calling functions

Working with Data
•Lists and tuples
•Dictionaries and sets
•File handling
Modules: Numpy & Matplotlib
• Modules and the import statement
• Plotting

Exception Handling
• Handling exceptions
• Raising exceptions
• Custom exceptions
Review and Practice

MONTH 4: Machine Learning

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. Become acquainted with GIS for Spatial Analysis

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

Bagging and Boosting
• Bayes’ Theorem
• Naive Bayes
• Decision Tree

GIS & Remote Sensing

MONTH 5: Machine Learning Engineering & Data Analytics

Learning Outcomes

  1. Learn how to deal with Regression Models
  2. Learn about Neural Networks
  3. Get an insight into Unsupervised Learning

Regression Models
• Linear Regression
• Logistic Regression

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

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

• Auto train the model, fine-tune it,
  and evaluate it on a given dataset
• Learn libraries like PyCaret and H2O

MONTH 6: NLP, Computer Vision & Job Market Preparation

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

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

Job Market Preparation
• Resume Building for Data Scientists
• Interview Preparation
• Portfolio Building & Demonstration

Job Market Preparation
• Resume Building for Data Scientists
• Interview Preparation
• Portfolio Building & Demonstration

MONTH 7: Capstone Project

All Weekends will hold:

- TA sessions for hand-holding support
- Guest lectures by International Data Scientists
- Real world data practice by the leading data science trainer


Meet our experienced data science instructors. Our curriculum is created and taught by Data Scientists with years of real-world industry experience.

Data Science Bootcamp Trainer

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.

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.

Data Science Bootcamp

Sidra Cheema professionally belongs to the technology industry, having worked for over 7+ years in consulting and solutioning which included data analysis and data science.

Machine Learning and Computer Vision Leader, specialized in deep learning and active learning with domain expertise in Climate Tech, Facial Identity, Medical Imaging and self-driving vehicles.
Experienced in delivering computer vision products and APIs for use cases including image recognition and classification, object detection and segmentation in 2D and 3D images/videos – application ranging from climate, satellite, medical, facial identity, self-driving vehicles, retail and fashion.

Yahya Bajwa is an experienced professional with a demonstrated history of working in the management consulting industry. He holds a Master of Public Policy (MPP) degree and a Graduate Certificate in Data Science from the Gerald R. Ford School of Public Policy, University of Michigan.

Minahil Raza’s work is focused on data analytics and energy and she has worked with organizations such as Asian Development Bank, the World Bank, London School of Economics, CERP and International Growth Centre.

Pricing Plans

Standard Monthly Plan

PKR 25,000 per month
  • Standard Monthly Program

Monthly Plan for atomcamp alumni & women

PKR 20,000 per month
  • Monthly Plan for atomcamp alumni & women

Lumpsum Payment (Advance Payment)

PKR 100,000
  • for 6 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?

While it is understandable that people from technical backgrounds will find it easier to grasp some of the concepts, this program is designed to be accessible to individuals from all sorts of backgrounds. The only requirement is that you be willing to work hard and are motivated. This Bootcamp is for anyone who is curious about data science and willing to explore, segment, analyze, and understand their data in order to make better data-driven decisions. 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.

What kind of jobs can I apply to after attending the Bootcamp?

Based on your skillsets, here are some job roles that you can target. Further information will be provided during our classes and speaker series.
· Data Engineer
· Machine Learning Engineer
· Data Analyst
· Data Scientist
· Product Analyst/Business Analyst