Course Artificial Intelligence with Python | ARTIFICIAL INTELLIGENCE duration Online
Even if we are not entirely aware of it, Artificial Intelligence is already part of our professional and personal life. In fact, everyone knows about driverless cars or voice assistants like Apple's Siri, Microsoft's Cortana or Google's Alexa, but, for example, business companies also use intelligent algorithms, able to self-learn, to suggest which products to buy, movies or music in line with our tastes, to filter CVs so as to select the ideal candidate. And so on.
If the knowledge of Python alone, being the most in-demand programming language in the world, is enough to arouse interest in companies, what recruiters are really looking for is someone who is able to manage data and extract a concrete meaning; multinationals, consulting companies, web agencies, advertising agencies, educational institutions and government are just some of the realities that require these skills.
The course aims to train on the theoretical and practical level professional figures dedicated, or who want to integrate in other areas, to Python programming, a versatile and powerful language, which this year rises to the first place of programming languages; to manipulation, transformation, analysis, and presentation of data through Python libraries, such as Pandas or Matplotlib; to the use of ready-to-use Machine Learning and Artificial Intelligence tools for Python such as Scikit or Tensorflow.
Module 1 | AI & Machine Learning with Python
Historical introduction on ML and AI, Algorithm types and problems, Accuracy and validation, Feature extractions, Linear regression, KNN, SVM, Decision trees, Unsupervised methods, Clustering, Introduction to neural networks.
Module 2 | Deep Learning with Python
Theoretical introduction to Neural Networks for Deep Learning, Python libraries for Deep Learning (Tensorflow), creation of a Neural Network and application to real datasets, Regression applied to different types of structured and unstructured data, such as numerical, categorical, or textual. Architectures of Neural Networks, such as Convolutional and Recurrent.
Details of each teaching unit will be provided during the first meeting
Pre-condition: curiosity, passion for technology and above all motivation.
The course requires basic programming knowledge in python; manipulation, transformation, analysis, and presentation of data through special Python libraries, such as Pandas or Matplotlib
Equipment and Note
At the end of the course you will know how to:
- program in Python language having a good overview of the language, being able to manage backend projects and having the right foundations to deepen different aspects on your own.
- manage data, know how to retrieve, filter, transform and present it, also in graphic forms, and will be able, for example, to create reports, inspect which customers are interested in which product, manage production or supply, etc..
- use the most widespread ML and AI techniques for applications such as: advertisement intelligence, finance, robotics, optimization, probabilistic prediction of future events, etc..
Notebook: 64-bit dual core CPU | 4GB RAM | S.O. Windows, GNU/Linux or macOS
NOTE: Academic hours of 50'.
Read the opinions of former students!
The ideal course for those who are interested in quickly absorbing notions of data mining and data manipulation in Python and integrate advanced forecasting models to their skills; very well structured, I recommend it to everyone because it has a practical cut that allows you to use the skills learned from the beginning, both at work (for data analyst/data scientist) and on a personal level, providing the tools to continue independently at the end of the course.
While knowing that in just three weekends it's impossible to go through all the contents related to machine learning, the course has managed to draw a precise and complete drawing of the supervised/unsupervised learning techniques available, stimulating the curiosity of those like me who are interested in going deeper.
A praise to the organization and preparation of the speaker, who captured the attention of the participants showing availability and deep knowledge of the topics.