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AI Engineer: Deep
Learning from Zero to PRO
Artificial intelligence is changing the world - learn how to harness this power. From Python basics to complex transformers and language models, our course is your key to real AI mastery.
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Complete training from scratch - master neural networks, LSTM, GPT-like models
Theory + practice - write your own models from scratch, train them on real data.
Only the right tools - TensorFlow, Keras, PyTorch and architectures.
Projects in portfolio - NLP, computer vision, text generation.
What does
an AI Engineer do
An AI Engineer develops, trains and implements neural networks and machine learning algorithms to solve complex problems.
Here are his key tasks
AI model development
building and training neural networks (Transformers, CNNs, RNNs, GPT-like models).
Data
processing
collecting, cleaning and preparing datasets for training.
Training and optimization
tuning hyperparameters, speeding up models.
Implementation in production
integrating AI into applications, cloud, APIs.
This course is ideal if you aspire to
Enter the profession of the future
We'll help you learn a new specialty from scratch and provide a solid foundation for a successful career start.
Master the creation and training of neural networks
You will be introduced to modern tools that allow you to turn data into clear and understandable results.
Work in a promising and in-demand field
We will explain the different directions in the field and help you increase your professional value.
Requirements to start the training
Basic Python programming skills are required to successfully complete the AI creation course.
Our experts are practitioners
in the field of AI development
Alexey Chernobrov
Data Monetization expert
Machine Learning and Data Science consultant
Mikhail Ivanov
Lead AI Researcher at NVIDIA
Expert in Transformer architectures and LLM.
Elena Smirnova
CTO of AI startup
Expert in Computer Vision and Generative Models
Dmitry Petrov
Senior ML Engineer at Yandex
Developer of industrial solutions in TensorFlow/PyTorch
Сourse program
Module 1: Welcome
  • Welcome
Module 2: Introduction
  • What is Artificial Intelligence?
  • What Comprises AI Tech? Relation between AI, ML & DL
  • Classical Programming vs Machine Learning
  • Understand Machine Learning with a Classification Problem
  • Input Data Representations
  • "Deep" in Deep Learning
  • Recap
Module 3: Intuition Behind ML/DL Algorithms
  • Intuition Behind a Shallow Machine Learning Algorithm
  • Intuition Behind a Simple Deep Learning Algorithm
  • Weights (or Parameters) of a Deep Learning Model
  • Activation Functions
  • Loss Functions
  • Optimizers (Gradient Descent)
Module 4: Tensorflow/Keras Fundamentals
  • Course Materials & Setup
  • First Project: Build Image Classifier by Training on Fashion MNIST Data
  • Tensorflow & Keras
  • Tensorflow Basics
  • Keras Basics
Module 5: Deep Learning for Computer Vision - Part 1
  • Intro to CNN's
  • Project: Build Image Classifier Model with CNN's
  • Data Augmentation
  • Transfer Learning: Feature Extraction from VGG16 Pretrained Model
  • Transfer Learning: Fine Tuning by Freezing base
  • Transfer Learning: Fine Tune Select Layers
  • Transfer Learning: Fine Tune All Layers
Module 6: Deep Learning for Computer Vision - Part 2
  • Advanced Deep Learning Concepts
  • Project: Build Image Classifier with Mini-Xception like Architecture
  • Project: Build Image Segmentation Model
Module 7: Deep Learning for Sequences: Intro
  • Recurrent Neural Networks (RNN) & Sequence Data
  • LSTM & GRU
Module 8: Deep Learning for Time Series Data
  • Project: Build Time Series Models to Forecast Seattle Bicycle Traffic
Module 9: Deep Learning for NLP: Part 1 - Sentiment Analysis
  • Intro to NLP - BOW, RNN, LSTM, GRU
  • Project: Sentiment Analysis on IMDB Reviews: BOW
  • Sentiment Analysis on IMDB Reviews: Sequence Models - BiLSTM
  • Transformers Architecture - Encoder
  • Sentiment Analysis on IMDB Reviews: Transformer Encoder
Module 10: Deep Learning for NLP: Part 2 - Translation
  • Translation: Encoder - Decoder with RNN
  • Translation: Encoder - Decoder with Transformers
  • Project: English to Spanish Machine Translation with GRU
  • Project: English to Spanish Machine Translation with Transformers
Module 11: Deep Learning for NLP: Part 3 - Text Generation
  • Text Generation: Decoder only Transformers
  • Project: Building our own Text Generation Language Model
  • Conclusion & Thank You
  • Acknowledgements & Further Reading
What you will learn on the course
Explore deep learning - from computer vision to time series analysis to NLP.
Learn to “see” like an AI - create neural networks for image recognition from scratch.
Learn the architecture of the first language models step by step.
Unravel the secret of Transformers - the basis of ChatGPT and modern multimodal AI.
Understand how to improve large language models.
You'll be able to train AI to generate text - from tone analysis to automatic translation.
Learn how to quickly translate AI ideas into code.
Practice each skill on real projects.
Certificate
After successful training and completed
assignments, you will receive a certificate of
advanced training, which will confirm your
competencies to your employer.
Choose the appropriate tariff
Introductory
  • Training program - 4 modules
  • Video lessons
  • Downloadable Resources
  • Homework
  • Assignment check
  • Mentor feedback
  • Access to the course - 1 week
  • Without certificate
$11
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Basic
  • Training program - 11 modules
  • Video lessons
  • Downloadable Resources
  • Homework
  • Assignment check
  • Mentor feedback
  • Chat for students and tutors
  • Access to the course - 2 months
  • Certificate
$69
Start Now
Standard
  • Training program - 11 modules
  • Video lessons
  • Downloadable Resources
  • Homework
  • Assignment check
  • Mentor feedback
  • Chat for students and tutors
  • Access to the course - 6 months
  • Certificate
$77
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Comfort
  • Individual mentor support
  • Training program - 11 modules
  • Video lessons
  • Downloadable Resources
  • Homework
  • Error analysis and recommendations
  • Chat room for students and tutors
  • Access to the course - 12 months
  • Certificate
$89
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Corporate
  • Groups of 5-10 people
  • Training program - 11 modules
  • Video lessons
  • Downloadable Resources
  • Homework
  • Assignment check
  • Mentor feedback
  • Chat for students and tutors
  • Access to the course - 6 months
  • Certificate
$830
Start Now
Why 9,000 people have already chosen our course
Actual Materials:
We provide up-to-date and useful training materials.
Practicing Experts:
Classes are taught by experts from leading companies.
Practical Skills:
Training is focused on real-world knowledge needed for the job
Career Prospects:
79% of our graduates are successfully placed in top companies within the first 3 months of completing the course.
What our Alumni say about the course
Anna K.
Data Scientist
After the course, I was able to get a job in an AI startup! Transformers projects were especially useful - now I'm working on improving the company's chatbot. Everything is explained from scratch, even complex topics become understandable.
Mikhail T.
Python developer
I never thought I would be able to create my own GPT model. The course gave me a clear roadmap: from basic Python to complex neural networks. Now I'm adding AI to my projects - my clients love it!
Daria S.
FinTech-analyst
I took the course to forecast time series (stocks, crypto). I immediately applied LSTM in practice - the accuracy of models increased by 30%. Better than any MBA!
Ivan L.
Product Manager
As a product, I am not a programmer, but the course helped me understand how AI solutions work. Now I can give accurate TORs to the team and even suggest ideas for ML-features. A huge leap in my career.
Artem V.
Student
From scratch to my first AI project in 3 months! I made a neural network for recognizing memes and won a hackathon with it. The instructors are practitioners from NVIDIA and Yandex, and give only up-to-date knowledge.
Return Guarantee
We remain flexible to meet your needs.
Therefore, we guarantee a full refund if you
change your mind within five days.
FAQ
What level of training is required to participate in the course?
Knowledge of Python basics (variables, loops, functions) and basic math (high school level) is recommended.
I have no experience in AI. Will I be able to get a job in the AI field after the course?
Yes! You will get a portfolio with real projects to show to the employer. Our students get jobs in IT companies,
startups and fintechs - even without previous experience in Data Science.
Can I combine my studies with work?
The platform is available 24/7, so you can attend classes at your convenience and study at your own pace.
We recommend that you dedicate 5-8 hours per week to studying.
What are my chances of getting a job after completing the course?
We have analyzed and found that 85% of students who complete our career change course successfully find a job.
Moreover, 79% of them get job offers in the first five interviews. In addition, 27% find a job without actively looking
for a job - employers contact them themselves.