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Join the world's most comprehensive and practical data science course to learn data science, machine learning, deep learning, and artificial intelligence (AI) !
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Are you ready for the Data Science Future?
Learn Data science from A to Z
Machine Learning & Deep Learning
Statistics and Mathematics
There is no data science course, program or bootcamp like this one anywhere in the world (we checked).
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.
We assume no prior knowledge. This program is beginner friendly. As long as you want to learn Data Science, we can teach you how! In addition, our pre-course assessment comes with suggested preparatory materials to set you up for success.
You’ll get an official AstroLabs Data Science Bootcamp Certification, upon completion of this 2 month intensive Data Science Bootcamp
Data Science A to Z, starting with coding in Python then move into advanced topics like Machine Learning & Deep Learning.
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
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
Basics of Data Science to Solve Problems
Getting answers to our data questions (the 5 stages of Data Science in practice)
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
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
Data Sourcing via Web Scraping
BeautifulSoup & NavigableString
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
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
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
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
Advanced Machine Learning
Go beyond the basics of Machine learning to apply cutting edge advanced applications
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
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
Matrices, Vectors, and Tensors
Calculus and Geometry
N-Dimensional Spaces, Gradients, and Integration and Differentiation
Set Theory, Propositional Logic, and Finite State Machines
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
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.
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.
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.
Our educational excellence is a community effort. When you learn at AstroLabs, you can always rely on in-house team of experts to provide guidance and support, whenever you need it.
Technology Director at Huephase
Dany Entezari is a software engineer with a decade of experience, focusing on cloud computing and informatics. He is a certified Agile practitioner with experience in training and mentoring teams. His most recent work was at IBM and the United Nations, where he currently leads the development of an educational platform. Dany also spent years in advertising working on innovative projects for global brands like Unilever, Honda, and The Coca-Cola Company. He has worked on projects involving Augmented Reality, Video Streaming, Computer Vision, Data Mining, and Distributed Systems. Dany is also authoring a book titled Mathematics for Programming to be published by O'Reilly Media.
Director of Marketing & Learning Programs at AstroLabs
Director of Marketing & Learning Programs at AstroLabs, leading marketing & courses at AstroLabs Academy. Previously worked at MBC, Namshi, and RBBI, and has professional expertise in Analytics, Digital Marketing, Full-stack Web Development, and Business Intelligence. BS Computer Engineering from American University of Sharjah and Google certified since 2012. Ahmad is also the author of the book "Timeless Digital Marketing".
Our graduates are from big companies, small companies, they are founders, career changers and lifelong learners. Join us and meet your tribe!
During the Data Science Bootcamp I built a machine learning model that can predict the probability of members renewing their membership or expecting any payment issues. This model gave Wellfit a 90% accuracy and allows the team to proactively engage with members before the payment is due, identifying any potential barriers or likely-to-churn users. This has helped us to improve the relationship with our members as well.
Business Strategy Lead at Wellfit
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.
Design & Branding Consultant - Group Origin
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
Software Engineer - Van Leeuwen Pipe & Tube Group
One of the best Data Science courses in the region. Professional instructors, rich content, and exceptional support. If you are new to this field and are looking for a crash course with hands-on experience, this is for you. Highly recommend!
Ahmed Al Haddad
Senior Supervisor - Emirates Global Aluminium (EGA)
Superb course for someone looking to understand and start working on Machine Learning. The course ensures a good balance to give a view of various structures within machine learning and going into depth of the models. The practical approach and the exercises support the learning. Requires commitment through the course otherwise easy to fall behind.
Energy & Performance Services - Siemens Smart Infrastructure
Participating in the Data Science and Machine Learning Bootcamp from Astrolabs is a great opportunity to learn, supported by experienced and knowledgeable instructors. For 2 months, you get to apply what you have learned on different projects and develop hands-on skills with a group of motivated, curious, and like-minded people.
Former Flight Attendant - Emirates
Get your brain ready to see data differently
Co-Founder - Retailorz
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.
Absolutely, we do run tailored versions of our courses for companies such as SONY, BCG, Ferrero or Chalhoub. You can contact us here to discuss your objectives and build a custom-made program for you and your team.
We may follow up with you via WhatsApp.
AstroLabs Dubai - JLT, Dubai (& Live Stream on Zoom)
Self-paced & 1-1 with the instructor on-demand
مسجلة مسبقا & دعم فردي مع المدرب
Admissions Closing : August 27
And shhh, don’t tell anyone. Once you complete the form below we’ll also send you a completely free mini-course to help get you started on your data science journey!
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