Machine Learning with Pytnon
AI Academy
-
Unlock the Power of Machine Learning with Python
Step into one of the most transformative fields of modern technology with our comprehensive two-part course in Machine Learning. Designed to serve both newcomers and experienced programmers, this program bridges the gap between foundational knowledge and advanced applications, ensuring that every participant gains valuable, career-ready skills.
Whether you are at the very beginning of your journey into Artificial Intelligence or seeking to strengthen and expand your current expertise, this program will provide you with the tools, techniques, and confidence needed to excel in today’s data-driven world.
The curriculum is structured into two intensive modules spread across approximately four months (90 hours) of training. Each module emphasizes practical learning, with more than 80% of the sessions dedicated to hands-on exercises, coding challenges, and real-world projects. By working with widely used software tools and Python libraries, you will not only understand the theory but also apply it directly to real data and case studies.
Throughout the course, participants will explore the full cycle of machine learning, from data preparation and model building to evaluation, optimization, and deployment. You will also gain exposure to advanced methods, such as deep learning and natural language processing, which are at the core of today’s AI innovations.
Guided by experienced instructors and industry professionals, you will join a collaborative learning environment that fosters experimentation, critical thinking, and problem-solving. By the end of the program, you will be equipped with a solid portfolio of projects and a strong skill set to pursue new opportunities in software development, data science, AI research, and beyond.
What you will learn
Part 1: Introduction to Machine Learning with Python (45 hours)
Delve into the fundamentals of machine learning with Python, covering essential concepts such as data preprocessing, model training, and evaluation. Gain hands-on experience through practical exercises that build a solid foundation for understanding algorithms and their applications.
Part 2: Advanced Machine Learning with Python (45 hours)
Dive deeper into cutting-edge machine learning techniques, exploring topics like deep learning, reinforcement learning, and natural language processing. Collaborate with industry experts and tackle real-world challenges, honing your ability to develop sophisticated machine learning models using Python libraries and frameworks.
| Days and Hours | Start Date | End Date | Hours per Week |
|---|---|---|---|
|
Monday & Wednesday, 19:00-22:00 |
09/02/2026 | 10/06/2026 | 6 |
Download the program flyer
Detailed Curriculum
This syllabus covers a comprehensive range of topics, from the foundational libraries in Python for machine learning to advanced concepts such as neural networks and recommender systems. It provides a well-rounded understanding of the key aspects of machine learning and its practical applications.
Libraries for Data Handling, Preprocessing, and Visualization in Python (NumPy, pandas, matplotlib, seaborn, scikit-learn)
- Complete Process for Creating a Machine Learning Application
- Overview of the entire process from data collection to model deployment.
- Data Processing Before Machine Learning
- Importance of data preprocessing before feeding it to a machine learning algorithm
- Handling missing data
- Dimensionality Reduction, Feature Extraction & Selection
- Techniques for reducing the number of features in a dataset
- Various Types of Machine Learning Algorithms and When to Use Each
- Supervised Learning
- Regression: Simple linear, polynomial, LASSO, etc.
- Classification: KNN, Decision Trees, Random Forests, Support Vector Machines.
- Ensemble learning.
- Unsupervised Learning
- Clustering: K-Means Clustering, Hierarchical Clustering, Density-Based Clustering
- Semi-supervised learning
- Reinforcement learning
- Evaluation of Machine Learning Models
- Techniques such as train-test-split, cross-validation, r2 score, accuracy, handling overfitting vs. underfitting, confusion matrix.
- Recommender Systems
- Introduction to recommended systems
- Collaborative Filtering and Content-Based Recommendation
- Neural Networks and Deep Learning
- Introduction to neural networks
- Overview of deep learning
About AI Academy
Experience the cutting-edge of Artificial Intelligence (AI) Technology through our comprehensive courses. Dive into the fascinating world of AI and explore the principles, algorithms and applications that power intelligent machines. Our courses are designed to cater to both beginners and professionals, providing a solid foundation in AI concepts and hands-on experience with industry-leading tools and frameworks. Discover the limitless possibilities of AI in various domains such as healthcare, finance, gaming and more. Join us and become equipped with the skills and knowledge to navigate the AI revolution and shape the future with transformative AI solutions.
Who should attend
The course "Machine Learning with Python" is designed for a diverse audience with varying levels of programming experience and interest in machine learning:
- Beginner Programmers: Individuals with basic programming knowledge or newcomers to Python. Those interested in understanding the fundamentals of machine learning and its application using Python.
- Intermediate Programmers: Programmers familiar with Python looking to deepen their understanding of machine learning concepts. Individuals who want to gain hands-on experience with building and evaluating machine learning models.
- Data Scientists and Analysts: Professionals working with data who want to expand their skill set to include machine learning using Python. Those seeking practical knowledge in implementing machine learning algorithms on real-world datasets.
- Software Developers: Developers interested in incorporating machine learning techniques into their applications using Python. Individuals looking to explore advanced machine learning concepts to enhance their software development skills.
- Business and IT Professionals: Decision-makers and professionals from non-technical backgrounds who want a comprehensive overview of machine learning with Python. Those aiming to understand the potential applications and impact of machine learning in their respective industries.
- Anyone Interested in Advanced Machine Learning: Individuals with a solid foundation in machine learning who want to explore advanced topics and stay updated with the latest advancements. Those interested in specialized areas such as deep learning, reinforcement learning, and natural language processing.
Do you need more information? Let's get in contact:
Shopping Basket ({{count}})
-
{{item.Title}}{{item.Description}}Price: {{item.Price}}Quantity: {{item.Quantity}}
