Last Call: Machine learning with Python KI AI and deep learning in 5 sessions

A five-session training program titled Machine Learning with Python, AI and Deep Learning will take place in late August and early September 2026, offering participants an introduction to artificial intelligence and its practical applications. Organized by heise academy, the sessions aim to provide foundational knowledge of machine learning techniques, including supervised and unsupervised learning, decision trees, reinforcement learning, and deep learning using frameworks such as Keras and TensorFlow. Each session runs for four hours, beginning at 9 a.m. and ending at 1 p.m., and includes hands-on exercises, demonstrations, and interactive discussions. The course is designed for individuals with basic programming experience, preferably in Python, who wish to explore the potential of machine learning in their projects. Participants will gain insight into different types of machine learning algorithms, learn how to apply AI solutions realistically, and acquire skills in data preprocessing, classical statistical methods, and neural networks using Python libraries such as NumPy, pandas, Matplotlib, and scikit-learn. The sessions will be led by an expert who will guide attendees through theoretical concepts, practical examples, and case studies beyond the scope of Python itself. The schedule for the five sessions has been set with specific dates and topics. The first session, scheduled for August 26, 2026, will focus on Python fundamentals and data preparation using NumPy and pandas. This will be followed by a session on September 9, which will cover data visualization with pandas and Matplotlib. On September 16, the focus shifts to the basics of supervised learning using scikit-learn. A session on September 23 will delve into decision trees, unsupervised learning, and reinforcement learning within the context of machine learning. Finally, the last session on September 30 will introduce deep learning and artificial neural networks using Keras and TensorFlow. Participants can attend all five sessions live or access recordings afterward. In addition to the live sessions, materials and exercise files will be available for review after each class. Questions raised during the sessions will be addressed directly in a live chat, allowing for immediate interaction between participants and the instructor. Attendees will also have the opportunity to engage in discussions with other participants throughout the course. The program is part of heise academy’s broader educational offerings, which include both live classroom sessions and video-based courses. Those who complete this classroom or combine it with three additional video courses will qualify for the Professional Pass, granting them access to the entire heise academy campus. This pass provides expanded resources and learning opportunities for professionals looking to deepen their expertise in software development and emerging technologies. The course emphasizes practical application alongside theoretical understanding, ensuring that participants can apply what they learn to real-world scenarios. By combining theory with hands-on experimentation, the program aims to help attendees develop a realistic perspective on the capabilities and limitations of artificial intelligence. It also seeks to address common misconceptions about AI's potential, providing a balanced view of its role in modern information technology. Registration for the sessions is open, and further details, including ticketing options and logistical information, can be found on the official website of the classroom. Interested individuals are encouraged to visit the site to secure their spot in one of the upcoming sessions. The course represents a structured approach to mastering key aspects of machine learning and deep learning, tailored for professionals seeking to integrate these technologies into their work.