atomcamp

Data Science Bootcamp

A comprehensive training that addresses essential components required for achieving success in the field of Data Science and Artificial Intelligence.

  • Online
  • 4 Months
  • Monday to Friday 7 pm to 9 pm PKT

Starting Date: 5th January 2024

Complete Our Bootcamp and Become Job Ready

We help our successful candidates find Jobs and Internships, and also provide guidance in discovering Freelance opportunities.

About This Program

Acquire the essential data science expertise required to become a highly desirable professional capable of creating substantial value in any organization.

01

Comprehensive Learning Journey

Embark on a learning journey that starts with the fundamentals of data and progresses to advanced AI concepts.

02

Mastery of Essential Tools

Immerse yourself in widely-used data tools and software applications.

03

Deep Dive into Machine Learning

Acquire a deep understanding of both foundational and advanced machine learning techniques.

04

Hands-On Learning

Gain practical experience through real-world industry projects, putting your skills to the test.

05

Professional Advancement

Receive expert guidance on crafting resumes, acing interviews, and effectively showcasing your abilities to potential employers.

EXCEL IN YOUR CAREER
WITH DATA SCIENCE BOOTCAMP

Strengthen your data skills and excel in your existing career.

Excel in Your Career
with Data Science Bootcamp

Strengthen your data skills  and excel in your existing career

Trusted by Leading Companies

How to become a Data Scientist?

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About this Program

Acquire the essential data science expertise required to become a highly desirable professional capable of creating substantial value in any organization.

Start to Finish Learning: Begin with data basics and rise to advanced AI topics.
Master Industry Tools: Dive into popular data tools and software.
All About Machine Learning: Grasp foundational to advanced ML techniques.
Practical Experience: Work on industry projects for hands-on practice.
Career Support: Guidance on resumes, interviews, and showcasing your skills.

Key Features​

Project Based Learning

Apply theory to real-world projects for practical proficiency.

Expert Instructors

Learn from industry professionals to gain practical insights.

Industry Ready Portfolio

Craft a portfolio that showcases your industry-ready data science projects.

Guidance & Support

Receive guidance and assistance in your pursuit of data science career opportunities. Skilled teaching assistants are there for you.

Speaker Sessions

Regular speaker series with industry professionals and hiring manager

1-on-1 Coaching & Mentorship

Receive individualized mentorship to navigate your way through your data science career.

Earn a Verified Certificate of Completion

Earn a data science certificate, verifying your skills. Step into the market with a proven and trusted skillset.

Job Guidance and Placement

Go from Learning to Earning

Interview Preparation

Interview workshops and mock interviews.

Job Search

We teach you strategies for unconventional job hunting

Community Building

We support you to build your network with data science professionals

Resume Building

How to build a professional CV and LinkedIn profile building

Curriculum

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 PowerBI for data visualization.

Data Literacy
• Data Types
• Data Life Cycle

Excel
• Data Cleaning
• Data Preparation

Excel Advanced
• Pivot Tables
• Basic Analysis

Data Analytics and Visualization on PowerBI

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

Loops
• For and while loops
• Break and continue statements
Functions
• 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
• SVM

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

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

AutoML
• 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.

NLP
• 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 industry leaders

Pricing Plans

Standard Monthly Plan

PKR 30,000 per month
  • Standard Monthly Program

Lumpsum Payment (Advance Payment)

PKR 100,000
  • for 4 Months

Lumpsum Payment (For Women and alumni)

PKR 85,000
  • for 4 Months

Frequently Asked Questions

We recommend investing 2 extra hours daily to dive into materials, ace assignments, and truly embrace the learning journey.

Classes run five days a week, ensuring an immersive and engaging learning experience.

Our bootcamp explores cutting-edge data science technologies, covering machine learning, data analysis, and essential programming languages.

Absolutely! Active participation is crucial, with 80% attendance required for certification.

Yes, participants dive into hands-on assignments, reinforcing learning and practical application.

Definitely! We actively support participants in securing internships or jobs, rewarding those who show exceptional commitment and engagement. 

A Bachelor’s Degree in various fields is accepted, including Computer Science, Engineering, Maths, Stats, Economics, and Business

Our bootcamp features live training sessions, providing real-time interaction with instructors and peers.

Fulfill attendance, engage actively, complete assignments, and demonstrate proficiency in the taught skills.

Regular attendance is encouraged, but we understand life happens. Communicate any issues, and we'll support your journey.

It covers essential math concepts, laying the groundwork for understanding and applying advanced data science and machine learning algorithms.

Yes, we host Teaching Assistant (TA) sessions for reviewing material, clarifying concepts, and addressing queries.

This series focuses on soft skills, industry awareness, and career readiness, ensuring you're well-equipped for success in data science.

We understand accessibility is key. Contact us at team@atomcamp.com for information on financial assistance or scholarships.

Fill out the application form below, and our admissions team will guide you through the next steps.

Apply Now