Navigate this learning path and discover the details of all the skills, knowledge, and training you need to become a well-qualified AI expert and a successful professional. You’ll also find information about job opportunities, what you’ll have the chance to learn, and the requirements for all the listed courses.
37 Courses
+ 278 Hours
+ 75 Case studies
- Career Opportunities
In recent years, companies across all sectors have recognized the immense hidden value within their data, unlockable through sophisticated Artificial Intelligence (AI) approaches. These encompass transformative techniques like Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision. Such fields empower organizations to uncover profound insights, automate complex tasks, and create intelligent systems by identifying intricate patterns, thus profoundly transforming established processes across virtually every business domain.
This widespread AI adoption has generated exponential demand for skilled professionals who can design, implement, and manage these cutting-edge solutions. The career prospects are exceptionally bright for those specializing in these advanced areas. This trend is set to continue, making it an attractive global profession for individuals passionate about data and eager to drive the next wave of technological innovation and societal advancements.
What You Will Learn
- Programming logic using Python
- Fundamentals of programming with Python
- Data manipulation and numerical computing with NumPy
- Data analysis and processing with Pandas
- Solid theoretical foundation in the core Machine Learning algorithms
- Practical use of scikit-learn, Pandas, TensorFlow, PyTorch, and Weka for Machine Learning applications
- Applying Machine Learning using Python, Java, and R
- Data preprocessing and feature preparation for Machine Learning models
- Evaluation of Machine Learning models using statistical methods
- Core concepts of statistics and linear algebra applied to Data Science and Machine Learning
- Building Machine Learning projects with no-code and low-code platforms such as Google Vertex AI, DataRobot, Obviously AI, BigML, Microsoft Azure, and Orange
- Understanding the role of statistics in Data Science and Machine Learning
- Association rule mining using real-world commercial datasets (e.g., retail, food services, and academic institutions)
- Financial data analysis and forecasting using Machine Learning models
- Natural Language Processing (NLP), including sentiment analysis, emotion detection, text classification, and LLM-based workflows
- Extracting and analyzing data from social networks such as LinkedIn and Facebook
- Working with real-world datasets for classification, regression, clustering, and association, including participation in real competitions (KDD, Kaggle)
- Data exploration, feature engineering, model training, and fine-tuning of Machine Learning models
- Data visualization and chart generation to support data understanding and decision-making
- Theoretical concepts and hands-on implementation of Artificial Neural Networks, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Self-Organizing Maps, Boltzmann Machines, Autoencoders, Generative Adversarial Networks (GANs), and Transfer Learning
- Computer Vision applications, including facial detection, facial recognition, object tracking, OCR, and image understanding using deep learning
- Deploying Machine Learning models on Google Cloud Platform (GCP)
- Accelerating Machine Learning workflows using NVIDIA RAPIDS and GPU computing
- Using Large Language Models (LLMs) such as ChatGPT to accelerate project development
- Goals
This learning path is designed to provide students with the foundational and advanced resources to achieve a professional profile in the expansive fields of Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing (NLP), and Computer Vision, alongside Data Science.
Through the development of essential skills and competencies vital for these domains, students will, upon completion, be proficient in identifying real-world problem requirements and architecting their own intelligent solutions leveraging Machine Learning, Deep Learning, NLP, and Computer Vision techniques, applicable to both academic research and practical business challenges.
- Prerequisites
No prior experience is required.
The Ultimate Beginners Guide to Python Programming
Learn the basics of Python programming language quickly and easily! Examples implemented step by step with exercises
The Ultimate Beginners Guide to Python NumPy
Master everything you need to know about NumPy for numerical analysis and scientific calculations! Solved exercises
The Ultimate Beginners Guide to Pandas for Data Analysis
Python for Data Science: Develop essential skills with Pandas, with practical exercises solved step by step
No-Code and No-Math Machine Learning
Machine learning for everyone! Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure and Orange!
Artificial Intelligence and Machine Learning: Complete Guide
Do you want to study AI and don’t know where to start? You will learn everything you need to know in theory and practice
Data Science and Machine Leaning Principles for Sciences
Learn the basics and principles of data and machine learning for scientific problems
Linear Algebra for Data Science and Machine Learning
Learn the fundamentals of Linear Algebra and apply them to Artificial Intelligence and Data Science
Python Programming for Biological Problems
Solve more than 30 exercises and 4 Biology projects using Python programming language! Step by step implementations
The Ultimate Beginners Guide to Python Virtual Assistants
Build your own virtual assistant using speech recognition and voice synthesizer! Step by step implementation
ChatGPT for Data Science and Machine Learning
Use ChatGPT to streamline the execution of Data Science, Data Analysis, Machine Learning, and AI projects
Deploying Python Applications on Google Cloud Platform
From Training to Cloud: Deploying Machine Learning Models on GCP with Python
Neural Networks in Python From Scratch: Complete Guide
Learn the fundamentals of Deep Learning of neural networks in Python both in theory and practice!
TensorFlow Hub: Deep Learning, Computer Vision and NLP
Build computer vision and natural language processing projects quickly, easily and with few lines of code!
The Ultimate Beginners Guide to Python Recommender Systems
Use collaborative filtering to recommend movies to users! Implementations step by step from scratch!
The Ultimate Beginners Guide to Natural Language Processing
Learn step-by-step the main concepts of natural language processing in Python! Build a sentiment classifier!
Natural Language Processing for Text Summarization
Understand the basic theory and implement three algorithms step by step in Python! Implementations from scratch!
Mining and Analyzing Facebook Data
Use Python, Data Science and Natural Language Processing techniques to extract data and analyze your Facebook page!
Mining and Analyzing LinkedIn Data
Apply Data Science and Artificial Intelligence techniques to extract and analyze your LinkedIn network
Master LLMs with LangChain
Modern Generative AI and NLP Solutions! Build real-world projects using advanced LLMs like ChatGPT, Llama and Phi
LLMs and AI Agents for Business
Master Generative AI with Real Case Studies and Build Professional Solutions using LangChain, CrewAI, Gemini, and More!
Mastering DeepSeek: Unlock the Power of the Next-Gen Free AI
Learn DeepSeek from Beginner to Advanced: Explore This Cutting-Edge Generative AI with Real-World Use Cases
The Ultimate Beginners Guide to ChatGPT and DALL-E
AI in Communication and Content Creation: A Step-by-Step Journey with ChatGPT! Stunning image generation with DALL-E!
Computer Vision Masterclass
Learn in practice everything you need to know about Computer Vision! Build projects step by step using Python!
The Ultimate Beginners Guide to Face Detection and Recognition
Detect and recognize faces from images, videos and webcam using Python language with OpenCV and Dlib libraries!
Optical Character Recognition (OCR) in Python
OpenCV, Tesseract, EasyOCR and EAST applied to images and videos! Create your own OCR from scratch using Deep Learning!
Motion Detection using Python and OpenCV
Implement a vehicle counter and a social distancing detector using background subtraction algorithms! All step by step
Object Tracking using Python and OpenCV
Implement 12 different algorithms for tracking objects in videos and webcam!
Master AI Image Generation using Stable Diffusion
Create stunning images using Generative Artificial Intelligence! Step by step with Stable Diffusion and Python!
Next-Level Images with Generative AI and Stable Diffusion
Mastering Professional Image Creation: Explore real projects with Artificial Intelligence using a Graphical Interface
Midjourney in 2 hours: Practical Guide for Beginners
Discover the artistic expressiveness of Midjourney in crafting visually remarkable images
Artificial Intelligence Video Generation
Explore the potential of Generative AI! Create stunning videos in various styles and formats
Generative Adversarial Networks (GANs): Complete Guide
Deep Learning and Computer Vision to implement projects using one of the most revolutionary technologies in the world!
Artificial Intelligence: Optimization Algorithms in Python
Learn how to build optimization algorithms from the ground up!
The Ultimate Beginners Guide to Genetic Algorithms in Python
Implement genetic algorithms from scratch to solve real world problems!
Bio-inspired Artificial Intelligence Algorithms
Genetic algorithm, differential evolution, neural networks, clonal selection, particle swarm, ant colony optimization
The Ultimate Beginners Guide to Fuzzy Logic in Python
Understand the basic theory and implement fuzzy systems with skfuzzy library! Step by step implementations
AI Application Boost with RAPIDS GPU Acceleration
High-speed and high-performance GPU and CUDA computing! Build Data Science pipelines 50 times faster