Course Data Science & AI with Python | ARTIFICIAL INTELLIGENCE duration Weekend
Data is the new gold! Due to technological development, the computerization and the widespread diffusion of the Internet, companies, both multinationals and SME, are collecting large amounts of data.
This data can provide a lot of valuable information: they can tell us, for example, which customers are interested in one product rather than another, what trends are emerging or becoming obsolete, which customers are about to switch to a competitor and why, or even what to expect with good confidence in the immediate future.
If just the knowledge of Python, 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 specialized in Python, a versatile and powerful language, which this year ranks up to the first place of programming languages. Furthermore, participants at the end of this course will be able to manipulate, transform, analyse, and present data through Python libraries, such as Pandas or Matplotlib and to use AI & Machine Learning tools such as Scikit and Tensorflow.
Module 1 | Python 4 Beginners
Learning unit to start programming with Python from the basics. Development environment setup, introduction to object-oriented programming paradigms, reserved words, syntax, instructions, lists, sets, dictionaries, comprehension, operators, functions, packages, classes, exceptions, lambda function, basic external modules, advanced data types, advanced modules, mathematics, scientific, input/output, write files, exceptions, errors, debugging.
Module 2 | Data Science with Python
Manage datasets with Pandas, Import and manipulate datasets, Basic statistics, Graph creation with Matplotlib, Exploratory analysis with Seaborn, Data preparation, Data cleaning, Normalization, Coding of categorical variables, Dummy variables, Date and time series management.
Module 3 | 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 4| 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.
What I will gain at the end of this course?
Essential requirement: curiosity, passion for technologies and above all motivation.
The course is also suitable for beginners. Basic computer knowledge will improve learning speed.
Request an individual interview to know the details of our Entry level modules.
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
NB: 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.
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.
The course was carried out in a very well organized manner and the teacher's explanations were really clear so as to be understood in the most complete way.
It is a very valid course and the lessons are held by high skilled teachers. Thanks to this course I acquired useful skills essential to improve my career.
The teachers are one of the strengths of this course, they are really prepared and available to listen and answer our questions at any time . The course is well designed, starting from the basics of programming up to deep learning techniques. The teachers provide well-written notes that are useful for a review and study at home. I recommend it to everyone!