Open Academy / Data Science

Data Science & Machine Learning Bootcamp

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Join the world's most comprehensive and practical program to learn data science, machine learning and deep learning!

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The AstroLabs Data Science, Machine Learning & Deep Learning Bootcamp

Are you ready for the Data Science Future?

Learn Data Science from A-Z with the most comprehensive data science, machine learning and deep learning program in the world!

Data science is on the rise, and for good reason. Over 2.5 quintillion bytes of data is created every day on the internet, but without Data Science, it's nothing more than 1's and 0's. Data Science is what helps organizations, governments and businesses use data to make informed decisions for a better world.

In order to teach you Data Science in a practical way from scratch, AstroLabs Academy has built an intensive 2 month part time Data Science & Machine Learning Bootcamp, built by and for professional practitioners. This Data Science Program is designed for the working professional and student. All sessions and material will be delivered after hours, to work around your schedule!

This practical program will focus on five main areas:

- Online Live Training On Core Topics
- Mentorship, and Office Hours sessions
- Remote Online Learning & Blended Learning
- Practical Projects with Real World Applications
- Open Coding & Pair Programming Sessions

The course will take place ONLINE LIVE fully remotely with the option to attend in-person at the AstroLabs Dubai JLT branch! By the end of the program, you will have strong practical experience using Data Science and will be well on your way to either get your first job in Data Science or level up your data talent stack to excel in your career.

No Program Like It

There is no program or bootcamp like this one anywhere in the world (we checked). We really believe this is the fastest and most comprehensive way to learn Data Science (from A-Z) through practical live instruction with a 0% chance of getting stuck!

Learn Practical Cutting Edge Technologies

This is a no-fluff program where we start learning to code in Python (the most famous language for practical Data Science), then towards the end of this 2-month program, we get into advanced topics like Machine Learning & Deep Learning

Fully Online Live Remote With Optional In-person Learning

Sessions are delivered fully remotely online, with the option to attend in-person. Participants will gain lifetime access to the AstroLabs online learning portal for regular updated content shared to help you on your Data Science learning journey.

AstroLabs Certification

You'll get an official AstroLabs Data Science Bootcamp Certification, upon completion of this 2 month intensive Data Science Bootcamp

Open To All Skill Levels

We assume no prior knowledge. This program is beginner friendly. As long as you want to learn Data Science, we can teach you how Data Science!

Career Opportunities

We'll connect you to our large network of relevant job opportunities as well as our in-house recruiters at AstroLabs Talent to support you get your first job or build on your successful career.

Tools

Platforms Covered

Content: Inside the Course

What you will learn

Practical, project-based. comprehensive, multi-disciplinary Data Science knowledge.

Module 1

Introduction to Data Science

Module 1

Introduction to Data Science

Learn the 5 stages of Data Science, how to get started with Python on your machine, and how to practically learn the immense field of Data Science

Introduction to using data in 2021
The 5 stages of the data science process and the four flavors of data analysis
Why choose Python (differences between Python and R)
Installing Python on our machine and using the terminal
Installing Visual Studio Code
Getting started with Python
Python for Data Engineering
R for Data Analysis
How Machine learning & Deep Learning works
How Deep learning neural networks Big data work
Understanding Predictive analytics and Prescriptive analytics
Business intelligence with data science using Sources of Data, Data Preparation, In-house data, Open data and APIs
Overview of Scraping data and Creating data
Passive collection of training data and Self-generated data

Module 2

Python Syntax

Module 2

Python Syntax

Learn the basics Python command and Syntax to program anything

Definition of Algorithms Definition of Data Structures
Hello world, Expressions and Statements
Blocks and scope & Conditionals
Functions and Objects
Variables and Data Types
Lists & Loops
Dictionaries
Frequency Tables
Algorithm Practice
Solving Algorithms
Basics of Data Science to Solve Problems
Getting answers to our data questions (the 5 stages of Data Science in practice)

Module 3

Data Structures

Module 3

Data Structures

Learn how data is structured and prepared in the context of data science

Tools for Data Science, Applications for data analysis and Languages for data science
Machine learning as a service, Data Visualization 101 and The three types of data visualization
Selecting optimal data graphics, Communicating with color and context Analyses for Data Science
Descriptive analyses, Predictive models and Trend analysis
Clustering, Classifying and Anomaly detection
Dimensionality reduction, Feature selection and creation, Validating models and Aggregating models
Data Preparation Basics Filtering and selecting
Treating missing values Removing duplicates Concatenating and transforming
Grouping and aggregation & Conditional Statemenets
Structured Data, Classes, Exceptions and String Objects

Module 4

Data Collection & Web Scraping

Module 4

Data Collection & Web Scraping

Learn about internal and external data importing, web scarping & the basics of data collection

The data collection process
Getting data in 1) Internal (Databases, CSV's, etc.) 2) External (API's, Web Scraping, 3rd Party services)
Practical Data Science Applications: Getting Data in using web scraping
How data scraping works on the web, Traversing the DOM, finding elements by class and ID & Avoiding detection when scraping
Mocking inputs / Pagination - Search and filters
Using sitemaps and robots.txt files & Error Handling
Saving, reading / writing to a file
Extracting data
Data Sourcing via Web Scraping
BeautifulSoup & NavigableString
Data parsing
Introduction to NLP (Natural language processing)
Cleaning and stemming textual data
Lemmatizing and analyzing textual data
Project- Scraping Yellow Pages
Project - Scraping Data from Job Sites

Module 5

Analysis & Visualization

Module 5

Analysis & Visualization

Learn how to perform data analysis and visualization in Data Science along with mathematical principles

Descriptive analyses and Predictive models
Regression, Clustering and Classifying
Anomaly detection, Dimensionality reduction, Feature selection and creation
Validating models and Aggregating models
Mathematics for Data Science: Algebra & Calculus
Optimization and the combinatorial explosion and Bayes' theorem
Acting on Data Science, Interpretability Actionable insights
Legal, ethical, and social issues of data science + Agency of algorithms and decision-makers
Collaborative Analytics with Plotly
Create statistical charts Line charts, Bar charts and pie charts
Opening files Text vs. binary mode
Using standard modules and Creating a module
Practical Data Visualization
Creating standard data graphics, Defining elements of a plot, Visualizing time series, Creating statistical data graphics

Module 6

Data Engineering

Module 6

Data Engineering

Learn how to engineer data through programming, mathematics and big data

Data Engineering Introduction
Definition of Big Data
Tools in Big Data
Overview of Apache Spark, Algorithms in Big Data
Scientific Python Overview
Ramp up with Scientific Python
Overview of Jupyter Notebooks & Overview of DataBricks
Start the notebook server, Use code cells, Extensions to Python language
Understand markdown cells, Edit notebooks
NumPy Basics Overview: NumPy NumPy arrays
Slicing Learn Boolean indexing
Understand broadcasting, Understand array operations, Understand ufuncs
Pandas overview, Load CSV files, Parse time
Use pure Python packages, Calculate speed, Display a speed box plot, Conda Overview

Module 7

Machine Learning

Module 7

Machine Learning

Learn to apply machine learning concepts within Data Science

Main Components of Machine Learning, Prediction (with Linear Regression)
Dimensionality Reduction (with Principal Component Analysis) & Density Estimation (with Gaussian Mixture Models)
Classification (with Support Vector Machine)
Programming & Mathematical Foundations
Fundamental Concepts of Machine Learning
Classification, Clustering, and Regression
Supervised Learning & Unsupervised Learning
Reinforcement Learning, Train/test and cross-validation & Accuracy metrics (RMSE and MAE)
Top-N hit rate: Many ways Coverage, diversity, and novelty
Churn, responsiveness, and A/B tests Review ways to measure your recommender Our recommender engine architecture K-nearest neighbors (KNN) and content recs
Deep learning introduction & Deep learning prerequisites
Basics of artificial neural networks, Introduction to TensorFlow and Introduction to Keras, CNN architectures & Intro to deep learning for recommenders, Restricted Boltzmann machines (RBMs), Recommendations with RBMs

Module 8

Advanced Machine Learning

Module 8

Advanced Machine Learning

Go beyond the basics of Machine learning to apply cutting edge advanced applications

Using DataBricks
Train/test and cross-validation, Accuracy metrics (RMSE and MAE),Top-N hit rate: Many ways
Coverage, diversity, and novelty
Churn, responsiveness, and A/B tests Review ways to measure your recommender Review the results of our algorithm evaluation
Content-based recommendations and the cosine similarity metric
K-nearest neighbors (KNN) and content recs, Producing and evaluating content-based movie recommendations, Bleeding edge alert: Mise-en-scene recommendations, Dive deeper into content-based recommendations, Measuring similarity and sparsity, User-based collaborative filtering & Item-based collaborative filtering
Tuning collaborative filtering algorithms
Evaluating collaborative filtering systems offline , Measure the hit rate of item-based collaborative filtering, Running user- and item-based KNN on MovieLens, Experiment with different KNN parameters, Bleeding edge alert: Translation-based recommendations, Principal component analysis (PCA), Singular value decomposition (SVD) Running SVD and SVD++ on MovieLens, Tune the hyperparameters on SVD
Playing with TensorFlow
Handwriting recognition with TensorFlow & Keras,, Classifier patterns with Keras, Predict political parties of politicians with Keras, Intro to convolutional neural networks (CNNs), Handwriting recognition with CNNs, Intro to recurrent neural networks (RNNs) Training recurrent neural networks Sentiment analysis of movie reviews using RNNs and Keras, Recommendations with RBMs
Tuning restricted Boltzmann machines
Auto-encoders for recommendations: Deep learning for recs, Recommendations with deep neural networks, Clickstream recommendations with RNNs Get GRU4Rec working on your desktop, Bleeding edge alert: Deep factorization machines
Introduction and installation of Apache Spark
Movie recommendations with Spark, matrix factorization, and ALS, Recommendations from 20 million ratings with Spark, Amazon DSSTNE , Scaling up DSSTNE
AWS SageMaker and factorization machines
Factorization machines on one million ratings, in the cloud, The cold start problem (and solutions) Implement random exploration,Stoplists , Filter bubbles, trust, and outliers Fraud, the perils of clickstream, and international concerns, Temporal effects and value-aware recommendations

Module 9

Advanced Mathematics for Data Science

Module 9

Advanced Mathematics for Data Science

Learn advanced mathematical concepts and how they map onto data science applications and libraries

Statistics and Probability Theory
Random Variables and Probability Distributions
Linear algebra
Matrices, Vectors, and Tensors
Calculus and Geometry
N-Dimensional Spaces, Gradients, and Integration and Differentiation
Discrete mathematics
Set Theory, Propositional Logic, and Finite State Machines
CAREER STARTERS, SWITCHERS & Learners

Who is it for?

Career starters

Are you someone who is starting out your career and understands how many different career options open up if you have strong Data Science skills? Finance, marketing, design, data analytics, science and way more. Rocket-launch your early career by learning essential and transferable coding skills.

Career switchers

Are you someone that has come to the party a bit late in realizing the power of leveraging Data Science? Firstly it is never too late to change (or add to) your career and secondly you’re not alone. Take ownership of the next phase of your career jungle gym and learn data science.

Career learners

Are you a non-tech person who wants to “lift the hood” on actually understanding how data science works? Demystify the jargon and manage complex data within any context by learning in-depth how data science, machine learning and deep learning work in the real world.

What is included?

2 month In depth comprehsive live modules held on Zoom / in-person in Dubai with one of our expert instructors

Office hours with instructors and mentors so you never get stuck

Over 75 hours of instruction, mentorship and projects

Online community forum to troubleshoot, collaborate, learn and chat with your classmates

Practical Data Science projects you can add to your portfolio and talent stack

A vibrant alumni community of the largest number of coders and digital experts in the region

instructors

Meet Your Practitioner Instructors

Expert practitioners that teach practical knowledge you can immediately implement.

7969

Danial Entezari

Technology Director at Huephase

Learn more

7089

Ahmad Abugosh

Director of Marketing & Learning Programs at AstroLabs

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Schedules

Upcoming Courses

Alumni

Our Graduates

Our graduates are from big companies, small companies, they are founders, career changers and lifelong learners. Join us and meet your tribe!

TESTIMONIALS

Alumni Reviews

The Astrolabs part-time Coding bootcamp is focused and current, teaching sought after skills around fullstack JavaScript. I never imagined that I’d be able to build a complete MERN stack application in 8 weeks, whilst still working full time. This bootcamp delivered beyond my expectations and cemented my desire to pursue web development.

Sajid Akhtar

Technology Director, Data Science Practice - Publicis Media MENA

For a beginner like me, the course was eye-opening and very interesting to learn. Instructors are helpful, knowledgeable, attentive to class needs and clear in explaining different types of codes and details. Very happy to be a part of this course and definitely need to keep learning.

Mustafa Aljuaidi

The environment was great. Instructors were super helpful and did everything in a timely manner, very flexible at all times. Everything I learned during this boot camp was very helpful to get me started on the process of learning web development and gave me just the right fundamentals and knowledge to move further and learn even more.

Aron Gabor

Abercrombie & Fitch Brand Representative

Troubleshooting our problems and walking us through them. Helping us every step of the way. Never leaving questions unanswered.

Mohamad Mahdi

CO Dulsco

The best thing was that I learned about coding and creating a website from scratch within 2 months. All the sessions conducted were informative and not only did I learn, I also applied what was taught in assignments and group projects.

Shreya Doshi

Vice President Public Relations

It feels good to be surrounded by like minded people who share the same passion, by mentors who guide you throughout the execution of your project, and other entrepreneurs who inspire and motivate you

Timothee Desurmont Van Leeuwen

Business Development Manager

John Bartlett

Coding Bootcamp Alumni

Lina El Husseini

Coding Bootcamp Alumni

Lajisha Latheef

Coding Bootcamp Alumni

Izzat Al Olwani Testimonial

Coding Bootcamp Alumni

Frequently asked questions

This Data Science & Machine Learning bootcamp will be conducted online live fully remotely (over Zoom and our own Learning Management portal) as well as optionally in-person at the AstroLabs JLT branch in Dubai. Our sessions blend practical knowledge with live coding to ensure that you learn practically by doing!

Yes, you will have lifetime access to video recordings for all sessions as well as additional recorded material when signing up for our Data Science bootcamp. You will also receive all future content updates (to make sure your knowledge is always on the cutting edge).

Upon completion of this course, you will receive the AstroLabs Data Science Bootcamp Certification (certified by the Dubai Government KHDA authority). By the end of the course, you will also have your own data science coding portfolio and of course a strong grasp of data science, which helps immensely in your career.

Although we cannot guarantee employment, several of our graduates have gotten jobs immediately after graduation. By joining this bootcamp, you'll be joining an active alumni network with exclusive access to opportunities we come across in our network and job portal as well as recruitment and career support through our in-house recruiters at AstroLabs Talent.

Yes, don't worry. As long as you have a passion for learning, beginners are welcome! Our Data Science Bootcamp starts from the basics and assumes no prior knowledge. However, we will require your commitment to learning, as data science is a topic that needs a lot of focus and practice!

One of the beauties of this program is that most of it is conducted via the browser (using Google Chrome), so as long as you have a laptop that was made in the last 5 years, you should be ok.

If you have any other questions, please reach out to us at [email protected]

We're a learning organization that has been helping people up-skill themselves since 2014. Our goal is your complete satisfaction with what we teach and we stand by that. If you are unsatisfied for any reason, you are eligible for a 100% money-back guarantee within 30 days of payment. All that we ask is for you to tell us how we can do better so we can improve.

Data Science & Machine Learning Bootcamp

Join the world's most comprehensive and practical program to learn data science, machine learning and deep learning!

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