Acquire Python Skills to Develop AI Solutions

Book your spot now and get 30% off!

Grab this chance to keep evolving with the job market. Your future self will thank you.

8 weeks

Remote

English

980€

1400€

Mon & Wed I 19.00 - 21.00 CET

SHORT PART-TIME AI COURSE (5-10 hours/week)

If optimizing AI/ML code, distilling insights from complex data, and applying deep learning to tech challenges interest you, this course sets you up to boost your projects and bring smarter solutions to your team. 

Acquire Python Skills to Develop AI Solutions

Aug 26 to Oct 16 

980€

1400€

-30%

Unavailable during these course dates?

Special price for a limited time only. Installment plans available.

Learn from anywhere you like! Plus, get real-time answers to your burning questions from an industry pro.

Showcase your new skills to employers with an Ironhack Certification.

Get access to premium accounts for all the tools you'll use during the bootcamp.

4.8/5 based on 2300+ student reviews

Upgrade your skillset: key course outcomes

Expand your toolstack

Harness AI Tools for Smarter Data Insights 

Tackle advanced AI challenges

Use Python to write efficient code for AI and ML applications, NumPy and Pandas to effortlessly navigate numerical data for AI, and Keras or TensorFlow to classify images from complex datasets.

Apply deep learning principles and neural network architectures to solve image classification and sequence processing tasks.

Decode complex data: enhance abilities in preprocessing, statistical analysis, machine learning algorithms, and natural language processing.

Who is this course for?

- Anyone with programming experience 

- Software developers, data analysts, and more! 

Are you ready for it? Check the prerequisites

- Programming experience in languages that cover variables, functions, lists, loops, and dictionaries.

What you'll learn in this course:

Introduction to Python and AI Basics

WEEK 1

Lecture 1: Introduction to Python Programming Language

Basic syntax, variables, and data types. Control structures: if statements, loops.

Lecture 2: Introduction to Artificial Intelligence

Definition and history of AI. Applications and significance in modern technology.

Lab: Write a Python script that simulates a basic AI chatbot. Implement if statements and loops to handle user inputs and generate responses based on predefined conditions.

Python

WEEK 2

Python Data Structures and Libraries

Lecture 3: Lists, tuples, and dictionaries in Python

Understanding data structures for AI applications.

Lecture 4: Introduction to NumPy and Pandas

Handling numerical data efficiently for AI tasks.

Lab: Utilize lists, tuples, and dictionaries in Python to implement a simple data storage and retrieval system. Use NumPy and Pandas to analyze a given dataset and generate insights through basic statistical analysis and visualization.

Numpy

Python

Pandas

WEEK 3

Introduction to Machine Learning

Lecture 5: Fundamentals of Machine Learning

Supervised vs. Unsupervised learning. Regression vs. Classification.

Lecture 6: Linear Regression with Python

Implementing simple linear regression using Python libraries.

Lab: Choose a small dataset (e.g., from UCI Machine Learning Repository) and apply linear regression using Python libraries to predict a target variable based on input features. Compare the results with different regression algorithms and evaluate their performance.

Python

WEEK 4

Machine Learning Algorithms

Lecture 7: Classification of Algorithms

Logistic Regression, Decision Trees.

Lecture 8: Clustering Algorithms

K-Means, Hierarchical Clustering.

Lab: Implement logistic regression and decision tree classifiers on a classification problem dataset. Evaluate the performance of each algorithm using appropriate metrics and visualize the decision boundaries.

Python

WEEK 5

Deep Learning Basics

Lecture 9: Introduction to Neural Networks

Structure and components of neural networks.

Lecture 10: Building Neural Networks with TensorFlow/Keras

Hands-on coding session on building and training neural networks.

Lab: Build a simple neural network using TensorFlow or Keras to classify images from a dataset (e.g., MNIST). Experiment with different network architectures and activation functions to optimize performance.

TensorFlow

Keras

WEEK 6

Advanced Deep Learning

Lecture 11: Convolutional Neural Networks (CNNs)

Understanding CNN architecture and applications.

Lecture 12: Recurrent Neural Networks (RNNs)

Applications in sequence data processing.

Lab: Implement a convolutional neural network (CNN) using TensorFlow or Keras to perform image classification on a more complex dataset (e.g., CIFAR-10). Fine-tune the model and visualize the learned features using techniques like activation maximization.

TensorFlow

Keras

WEEK 7

Natural Language Processing (NLP)

Lecture 13: Introduction to NLP with Python

Text preprocessing, tokenization, and stemming.

Lecture 14: Sentiment Analysis with NLP

Building a sentiment analysis model using NLP techniques.

Lab: Preprocess a corpus of text data (e.g., movie reviews) by tokenizing, removing stopwords, and stemming. Train a sentiment analysis model using NLP techniques and evaluate its performance on a test dataset.

Python

WEEK 8

Final Projects and Applications

Lecture 15: Project Presentation Guidelines

Guidelines for final AI project presentation.

Lecture 16: Final Project Presentations

Students present their final AI projects, showcasing their understanding and skills.

Lab: Work on a final AI project that integrates concepts learned throughout the course. Choose a real-world problem or dataset related to Python, machine learning, deep learning, or NLP, and develop a solution using appropriate techniques. Present your project in a report or presentation format, highlighting the problem statement, methodology, results, and insights gained.

Python

NumPy

Pandas

TensorFlow

Keras

Disclaimer: Course topics are subject to change according to the demands of the job market.

Flexible payment plans to suit your budget

Spread your course fees over three manageable payments, without worrying about extra costs.

PayPal Pay Later offers you the flexibility to spread your payments over 3 to 24 months or enjoy the convenience of buying now and paying later.

Master in-demand skills with expert guidance

Dive into a curriculum approved by AI experts from Zylon by PrivateGPT, Clibrain, Vernon, and Diverge, crafted for your success in the field!

Get real-time help and learn directly from industry professionals who practice what they preach. Our instructors bring their daily experiences to the virtual classroom, offering insights you can't find anywhere else.

Learn by doing: work on projects with real-world applications

Dig into practical use cases of AI with this hands-on course. You'll be able to update your portfolio with new projects that highlight your fresh skills. 

Each lesson is designed for immediate application, ensuring you can transfer your new skills to your job without delay.

Enhance your learning with AI assistance and community support

Fit learning around your busy life

Grow your network in our Slack hub

Get 24/7 support

Missed something? Catch up with our recorded lessons, including summaries and Q&As, whenever you need a refresh or deeper dive. Easy, flexible learning at your fingertips!

Stuck? Your teacher and classmates are here to help live, and when they're catching a break, our friendly AI chatbot has got your back. Keep the learning going, anytime, anywhere!

Share projects or opportunities, seek advice, or chat about AI—our community awaits with open arms. Jump in and discover possibilities to boost your career!

Make potential employers take notice with a shiny new certification

Upgrade your resume and LinkedIn with an Ironhack certification and see how you stand out in the sea of applicants!

It’s the professional edge that makes employers stop and take a second look.

Don’t just take our word for it

“Ironhack Remote prepared me for the job market...After being motivated to work on products that could bring innovation to everyday life.”

Sr UX Product Designer at Zolar

“Really fulfilling. The instructors are genuinely interested in helping us, to know who we are and support us.”

Cybersecurity Analyst at NTT Security Holdings

“I chose Ironhack because the level is very high...it exceeded all my expectations. Studying there changed my life at all levels.”

Gabriel Ayela

Clemence de Robert

Nuno Moreira

Product Designer at Front

Ironhackers now work in:

FAQs

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What is the time commitment for this course?

This course requires a commitment of 5 to 10 hours each week, featuring teacher-led classes that smoothly transition into hands-on exercises. These practical activities are flexible, allowing you to tackle them whenever it fits your schedule throughout the week. You'll be pleasantly surprised to see the incredible progress you can achieve in just 8 weeks!

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How do Live classes work?

Our classes are led by professionals who are experts in their subjects, ensuring you have the opportunity to ask questions in real time and get industry insights. And if you ever miss a class, don't sweat it—we record each one, so you can watch at your leisure and stay on track with your hands-on exercises.

Will I get an official certificate at the end of the course?

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Ironhack provides a private certificate that you can use to showcase your new skills to potential employers. It's proof that you attended at least 80% of the classes, submitted at least 80% of class exercises, and demonstrated proficiency with the material. 

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I'm not sure I meet the prerequisites. What do I do? 

Contact us and we can help you to know if the course is the right fit for you.

Can I pay in several installments? What are the interest rates?

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We offer 3 interest-free installment payments to our customers in Spain, France, Germany, Portugal, Netherlands, Italy, Austria, Belgium, and Finland. If you don't see your country of residence in the list, hang tight! We're working on expanding this option to other countries soon. So don't forget to keep checking in for updates.


If you're in Spain and prefer to pay in installments, you have options with Banc Sabadell or PayPal Pay Later. With Banc Sabadell, you can choose from 3, 6, 10, or 12-month plans. Keep in mind, there are some bank fees: 2% for 3 months, 2.9% for 6 months, 4.3% for 10 months, and 5% for 12 months. We'll make sure to keep you informed about any extra fees throughout the process. If you're looking to avoid interest, PayPal Pay Later offers a way to split your payment into 3 manageable installments.


For those of you in France, PayPal Pay Later offers a convenient option to pay in 4 installments, completely interest-free.


And if you're in Germany, PayPal Pay Later provides flexibility with 3, 6, or 12 monthly installments at an interest rate of 12.99%, or you can choose 24 monthly installments at a slightly lower rate of 11.99%.


Contact us if you need more information. 

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How does the admissions process work? 

Our courses are designed with working individuals in mind, so there's no complicated admissions process to go through. Just take a moment to check the prerequisites to ensure you meet them. Then, signing up is as easy as 1-2-3:

1. Complete and submit the form.

2. Make your payment.

3. Look out for a welcome email with course details as well as an email to activate your Student Portal, where you will have access to course materials.

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Are there other course dates available?  

We will be running new courses every 2 months. Contact us for more details.

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Is there prework?  

Our AI School short courses are designed for ease of access, meaning there's no prework required. Simply sign up, and you're ready to dive in on Day 1! Just make sure to review the prerequisites beforehand to ensure you have the necessary background knowledge to participate fully.

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Do I need my own laptop?  

Every Ironhacker needs their own computer, but you don't need the latest iMac to get the job done!


For our AI School short courses, you'll need:

-Processor: A modern multi-core CPU (e.g., Intel i5 or higher, AMD Ryzen 5 or higher).

-RAM: At least 8GB (16GB or more is preferable for larger machine learning projects).

-Storage: A solid-state drive (SSD) with adequate storage. We recommend a minimum of 50GB but 256GB for faster data access.

-GPU (optional but recommended): A dedicated NVIDIA GPU (e.g., GTX 1060 or higher) for deep learning tasks.


Note: If you're using a device that doesn't belong to you (e.g., a company computer), you'll need to be granted full admin rights.

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Do you offer specific plans for companies?  

Absolutely, we offer specialized plans tailored for companies and organizations!


If you're looking to bring our courses into your company, we're here to help you every step of the way. Just reach out to us, and we'll provide personalized assistance.


We'll craft a plan that perfectly aligns with your training needs and the number of employees you wish to upskill, ensuring it fits your unique situation just right.

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Can my company pay for the course?  

Sure thing! Simply provide your company's payment information, and we'll send you an invoice.

I've read the entire page, including FAQs, but I still have questions. Who can help me?  

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Feel free to reach out to us via email at ai-info@ironhack.com and we'll get back to you within 3-5 working days. 

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