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Code is art / Est. 2015
Deep Learning and Artificial Intelligence Engineering Bootcamp in Barcelona Code School
1:1 Online Mentored Bootcamp
What is Machine Learning Engineer?
A Machine Learning Engineer designs, builds, productionizes, optimizes, operates, and maintains ML systems.
Our course is focused primarly on using ML for building Artificial Intelligence systems.
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Course format
Online, Mentored, 1:1, Part-time
- 13 weeks duration
- Can be done part-time
- Get text and video materials upfront to have flexibility when to study during the day
- Mentored and guided
- Support platform to get help
- Regular 1:1 sessions with your mentors
- The course is taught in English
- Modern curriculum with all the latest development in machine learning and AI
- A graduate certificate
What you'll learn
- Artificial Intelligence development with BERT, GPT, diffusion models, neural radiance field (NeRF)
- Reinforcement learning
- Language models and transformers
- Artificial, convolution, recurrent and generative neural networks
- Machine learning, tree models, K-means clustering
- Advanced Programming with Python
- Data Loading, Data Wrangling, Data Visualization
Tools
- Python
- Jupiter
- Matplotlib
- Pandas
- Tensorflow
- Tensorboard
- Scikit-Learn
The outcomes
- Get hired!
After the bootcamp you will be able to start working as a junior engineer. Possible job titles would be:
- Artificial Intelligence Engineer
- Deep Learning Engineer
- Deep Neural Networks Engineer
- Natural Language Processing Engineer
- Data Scientist
- Machine Learning Engineer
- Data Engineer
- Computer Vision Engineer
- Voice and Audio Processing Engineer
- Enter the most cutting edge and fast-growing IT field with a portfolio of completed projects done during the bootcamp showcasing your practical skills!
Curriculum breakdown
Module 1: Python
In the first module we will reinforce the basics of Python and introduce you to 2 fundamental data management and data visualization tools: Pandas and Matplotlib.
By the end of this module you will be able to load data, explore it, clean it and visualize it in interesting ways.
Module 2: Classical ML, Tree-Based Models, K-Means Clustering and more...
You will learn some of the ML models that every Deep Learning Engineer and Data Scientist should know with a mix of both theory and practice.
Module 3: Intro to Neural Networks / TensorFlow
During this module we will introduce you to Neural Networks, Deep Learning and TensorFlow.
You will learn almighty Gradient Descent, Back Propagation, optimization methods for Deep Learning. You will gain a solid understanding of TensorFlow and TensorBoard.
Project suggestions: we will start working on a MNIST handwritten digit database.
Module 4: Recurrent Neural Networks & Convolutional NN
This module you will be introduced to Convolutional and Recurrent Neural Networks, and various visual (like object detection, recognition, segmentation) and text (sentiment analysis, text classification) analysis techniques.
Project suggestions: NLP (spam recognition, sentiment analysis, text classification), CV (object detection, background detection, object counting and tracking).
Module 5: Generative Neural Networks (GANS and VAE)
In this module we will start digging into more advanced concepts of ML, GANs (General Adversarial Neural Networks) and VAEs (Variational Autoencoders).
It is of the utmost importance that you become capable of implementing your own networks. In this module we will let you follow through a few selected papers and implement such networks from scratch.
Project suggestions: image colorization, text-to-image synthesizer, noise reduction, new human pose generation.
Module 6: Language Models & Transformers
In this module we will learn about the most important advancement of the last 4 years in Deep Learning: Transformers. We will also understand why they perform the way they do, and what are their limitations. We will work with Transfer Learning and Model Tuning to speedup model development.
We will implement the famous paper “Attention is all you need”, and a few other selected papers.
Project suggestions: chat bot, object detection with vision transformers.
Module 7: Final Project / Intro to modern AI (BERT, GPT, Diffusion Models, NeRFs, Data Annotation, deployment)
This is your time to shine! Develop your own unique project, or follow one of the pre-prepared tasks.
Projects suggestions: object video tracking, text to audio system, depth/volume extraction from image, translation chatbot.
Your mentor
Dr. Minerva Singh
Minerva holds a PhD from the University of Cambridge, MPhil from the School of Geography and Environment and an MSc from the Department of Engineering at Oxford University. With over a decade of experience in academic research, Minerva has contributed to renowned peer-reviewed journals like PLOS One, showcasing expertise in data science, deep learning, and earth observation (EO) for both non-governmental and industry stakeholders.
With strong track record in machine learning, data visualization, spatial data analysis, deep learning, and natural language processing using R and Python combined with many years of mentoring experience Minerva is the best instructor for this bootcamp.
Specializing in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others Minerva has a valuable real world experience to share with the students.
Minerva also has acted as a peer reviewer on highly regarded academic journals such as Remote Sensing and given guest lectures on prestigious forums such as Open Data Science Conference (ODSC).
Prerequisites
Python: We will provide you with a Python videocourse which starts from the basics and takes you to the advanced level. It contains about 7 hours of video lessons and around 100 of exersies with tests for you to practice in case you need to level up your Python.
Tuition
3950€
900€ paid upon registration, the remaining is due before course begins.
Financing
We can assist in getting a student loan which usually have lower rates than consumer loans.
To do so we can send you a proforma invoice for the selected course which you can attach to the student's loan application.
Please fill out this form.
Instalment payments are available at the checkout
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How to join the bootcamp
- Choose the starting date and register online with 900€ payment which is part of the tuition ↴
- Fill out the student's form ↴
- Receive the prep materials ↴
- Join our Slack workspace ↴
- Start preparing ↴
- Make the remaining payment due 5 days before the starting date ↴
- On day 1 receive the workflow instructions and main materials to start working on the course, submitting your work and booking your 1:1 sessions.
Access.
December 2 – February 28, 2025
Deep Learning and Artificial Intelligence Engineering Bootcamp
Format: online
Tuition: 3950€
Become a ML/AI Engineer in 13 weeks
13-week course, online, mentored, in English, part-time.
Registration prepayment 900€.
January 6 – April 4, 2025
Deep Learning and Artificial Intelligence Engineering Bootcamp
Format: online
Tuition: 3950€
Become a ML/AI Engineer in 13 weeks
13-week course, online, mentored, in English, part-time.
Registration prepayment 900€.
International students
You are welcome!
A lot of our students are taking the course from abroad. Since this bootcamp is completely remote, you can join it from anywhere in the world!
Why Barcelona Code School?
- Cutting edge curriculum tailored to job market and companies’ needs
- Best students/mentors ratio
- Instructors, who know how to teach
- Fast track from beginner to job-ready coder
- Job support for the graduates
- Life-time career support
- Premium location – cozy campus in the downtown of Barcelona away from the touristic crowds
Why Machine Learning and AI?
- According to the latest HackerRank survey the most in-demand skills in the job market in 2022 were (ordered by volume):
- 1. Problem Solving
- 2. Machine Learning
- 3. REST API
- 4. React
- 5. HTML/CSS/IS
- 6. Data Wrangling
- 7. Node.is
- 8. Data Visualization
As you can see Machine Learning and Data Engineering fields are among the top in-demand in the market.
- Data science-related skills are the biggest gainers in the same survey, show that there is more and more demand for Data Engineers.
- Recent exponential progress in the AI engineering field means spike in demand for the Data Engineers as now technology allows more business start using AI.
FAQ
What computer would I need?
Any operating system will do, Mac, Windows or Linux. If you are thinking about buying a new one then the best choice would be an Apple laptop: Macbook, Macbook Air or Macbook Pro. On Windows laptop everything is doable as well, simply some things work slower on Windows but it's not going to prevent you from succeeding!
What is the language of this course?
English.
Do I have to speak Spanish?
For the course you do not need Spanish. Everybody at our school speak English. To feel comfortable in Barcelona Spanish would help but nowadays in most of the places local people do speak English.
What qualification I will get from this course?
After succesfull completion you will become a junior Machine Learning and Artificial Intelligence Engineer and will be able to apply for any relevant entry engineering positions.
How good would a typical graduate be after completing the course?
You will be able to work in Machine Learning, Deep Learning, AI development as a junior engineer.
Is there a pre-course?
Yes! We will send you some training materias to complete before the bootcamp.
How does your price compare to other schools?
It’s safe to say that our price is within lower competitive range. We strive to provide the personalized approach thanks to smaller group size and attract highly qualified instructors motivated to share their expertise with students. You will love it, we guarantee!
Inquiry about the course
Some of the companies where our graduates work or worked
