Introduction to Data Science, AI, and Machine Learning with Python - 3rd Edition (2025)

This intensive 24-hour training course offers an in-depth overview of the fundamental concepts and practical applications of Data Science, Machine Learning, and Neural Networks, and more generally of extracting value from a dataset. Through a combination of lectures and hands-on sessions, participants will acquire essential skills to tackle complex real-world challenges using Python as their primary language.
The course focuses on various algorithmic data analysis techniques, including regression, classification, clustering, and neural networks. Starting with the basics, participants will be guided through the fundamental concepts of each topic and introduced to a broad range of techniques and algorithms commonly used in Data Science and Machine Learning.

Through hands-on exercises and guided projects, participants will have the opportunity to apply their acquired knowledge to real-world datasets, tackling regression problems for forecasting, classification for analyzing categorical data, clustering for pattern identification, and deep neural networks for more complex machine learning tasks.
The entire course is taught using Python as the primary programming language, and participants are required to have a minimum level of programming proficiency to actively participate in the hands-on sessions. By the end of the course, participants will have a solid understanding of the fundamental principles of data science and machine learning, along with the ability to apply this knowledge in real-world contexts using Python.

Relevance and impact of the course in the tourism, fashion, culture, and textile industries. In general, data science and machine learning can be extremely useful in the tourism, culture, fashion, and textile manufacturing industries in several ways:

• Customer data analysis: Through customer data analysis, companies can better understand their customers' behaviors, preferences, and needs. For example, they can use machine learning techniques to analyze demographics, past purchasing patterns, and other behaviors to personalize offers and improve the overall customer experience.

• Demand forecasting: Companies in the tourism, fashion, and textile manufacturing industries can use machine learning algorithms to predict future demand for certain products or services. This allows them to optimize production, plan distribution more efficiently, and ensure sufficient resources are available to meet expected demand.

• Inventory Management: Through the analysis of historical sales data and the use of machine learning algorithms, companies can optimize inventory management. This means maintaining the right balance between supply and demand, minimizing waste and maximizing profits.

• Personalization of Services and Products: Data science can be used to create personalized customer experiences in the tourism, culture, fashion, and textile manufacturing industries. By analyzing data on user behavior and individual preferences, companies can offer personalized recommendations, product recommendations, or experiences tailored to meet each customer's specific needs.

• Market Trend Forecasting: Using data analysis from sources such as social media, search engines, and past purchasing trends, companies can identify and anticipate market trends in the fashion and textile industries. This allows them to quickly adapt their production, marketing, and distribution strategies to keep pace with emerging trends.

• Supply chain optimization: Data analytics can help optimize the supply chain in the textile manufacturing industry by identifying potential inefficiencies and bottlenecks. This can lead to greater operational efficiency, reduced costs, and faster delivery times.

In summary, data science and machine learning offer numerous opportunities to improve operational efficiency, optimize business decisions, and deliver more personalized and satisfying customer experiences in the tourism, culture, fashion, and textile industries.

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Course duration: 24 hours

3 days of 8 hours (9:00-18:00)

October 1 - October 8 and October 15

Course language: Italian

Delivery method: In-person

Minimum number of participants: 5

Maximum number of participants: 10

Registration fee: €450