Data Science Bootcamp

An in-depth, hands-on course on applying Data Science, Machine Learning, and GIS to Real Estate. It covers Python, Pandas, and Scikit-Learn for analyzing and forecasting property globally.

Python for Data Science and Machine Learning Bootcamp

In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).Data science can be defined as a blend of mathematics, business acumen, tools, algorithms, and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.In data science, one deals with both structured and unstructured data. The algorithms also involve predictive analytics. Thus, data science is all about the present and future. That is, finding out the trends based on historical data which can be useful for present decisions, and finding patterns that can be modeled and can be used for predictions to see what things may look like in the future.Data Science is an amalgamation of Statistics, Tools, and Business knowledge. So, it becomes imperative for a Data Scientist to have good knowledge and understanding of these.With the amount of data that is being generated and the evolution in the field of Analytics, Data Science has turned out to be a necessity for companies. To make the most out of their data, companies from all domains, be it Finance, Marketing, Retail, IT or Bank. All are looking for Data Scientists. This has led to a huge demand for Data Scientists all over the globe. With the kind of salary that a company has to offer and IBM is declaring it as the trending job of the 21st century, it is a lucrative job for many. This field is such that anyone from any background can make a career as a Data Scientist.In This Course, We Are Going To Work On 50 Real World Projects Listed Below:Project-1: Pan Card Tempering Detector App -Deploy On Heroku

Academy of Computing & Artificial Intelligence proudly present you the course "Data Engineering with Python". It all started when the expert team of Academy of Computing & Artificial Intelligence (PhD, PhD Candidates, Senior Lecturers , Consultants , Researchers) and Industry Experts . hiring managers were having a discussion on the most highly paid jobs & skills in the IT/Computer Science / Engineering / Data Science sector in 2021. At the end of the Course you will be able to start your career in Data Mining & Machine Learning. 1) Introduction to Machine Learning - [A -Z] Comprehensive Training with Step by step guidance2) Setting up the Environment for Machine Learning - Step by step guidance  [R Programming & Python]3) Supervised Learning - (Univariate Linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines (SVM), Random Forest)4) Unsupervised Learning5) Convolutional Neural Networks - CNN6) Artificial Neural Networks 7) Real World Projects with Source Course Learning Outcomes To provide awareness of  (Supervised & Unsupervised learning) coming under Machine Learning (Why we need Data Mining & Machine Learning, What is Data Mining, What is Machine Learning, Traditional Programming Vs Machine Learning, Steps to Solve a Data Mining & Machine Learning Problem, Classification , Clustering)Describe intelligent problem-solving methods via appropriate usage of Machine Learning techniques.To build appropriate neural models from using state-of-the-art python framework.To setup the Environment for Machine Learning - Step by step guidance  [R Progra

Data Science , Machine Learning : Ultimate Course For All Course Description:Welcome to the ultimate Data Science , Machine Learning course for 2025 – your complete guide to mastering Data Science , Machine Learning from the ground up with real-world examples and hands-on projects.This course is designed for beginners and intermediate learners who want to dive deep into the fields of Data Science , Machine Learning. Whether you’re starting from zero or brushing up your skills, this course will walk you through all the essential concepts, tools, and techniques used in Data Science , Machine Learning today.You’ll begin by understanding the core principles of Data Science , Machine Learning, then move into Python programming, data preprocessing, model training, evaluation, and deployment. With step-by-step explanations and practical exercises, you’ll gain real-world experience in solving problems using Data Science , Machine Learning.By the end of the course, you’ll be fully equipped to handle real projects and pursue career opportunities in Data Science , Machine Learning confidently.Class Overview:Introduction to Data Science , Machine Learning:Understand the principles and concepts of data science and machine learning.Explore real-world applications and use cases of data science across various industries.Python Fundamentals for Data Science:Learn the basics of Python programming language and its libraries for data science, including Num Py, Pandas, and Matplotlib.Master data manipulation, analysis, and visualization techniques using Python.Data Preprocessing and Cleaning:Understan

No Prior Experience Needed – Learn with Real Projects!Are you curious about Data Science & Machine Learning but don’t know where to start? This beginner-friendly bootcamp is your perfect first step! We’ll guide you from absolute zero to building real-world projects—no math or coding background required!What You’ll Learn:Python for Beginners – Learn from scratch with easy-to-follow examples Data Science Essentials – Pandas, Num Py, and data visualization (Matplotlib & Seaborn) Machine Learning Made Simple – Predict trends, classify data & uncover patterns Hands-On Projects – Work with real datasets (sales predictions, customer behavior, and more!)AI & ChatGPT Basics – Get introduced to cutting-edge tools like LL Ms (Large Language Models) Why This Course?Perfect for Beginners – Starts slow, explains every step, and builds confidence Learn by Doing – No boring theory—just fun, practical projects you can showcase No Experience Needed – We teach Python & math basics along the way Supportive Community – Get help whenever you’re stuck Certificate of Completion – Boost your resume with a valuable skill Who Is This For? Total beginners who want to explore Data Science & AI Students & professionals looking for a high-income skill Career changers curious about tech jobs Anyone who wants to future-proof their skills in 2025! Tools You’ll Use (No Setup Hassle!): Python (easy-to-learn) Jupyter Notebooks (user-friendly coding) Scikit-Learn (simple ML models) ChatGPT & AI tools (see how they work!) Bonus: Downloadable exercises & solutions Cheat sheets & study guides Lifetime access & updates Start Your Data Science Journey Today – No Experience Needed!

Unlock the power of interactive data science with Interactive Data Science in Python — a comprehensive, beginner-friendly course designed to take you from novice to confident practitioner. We begin by exploring Shiny, the dynamic and popular web app framework for Python, where you'll learn how to build interactive dashboards, responsive data visualizations, and user-friendly interfaces using the classic Shiny library. Once you’ve gained solid skills, you’ll transition smoothly to Shiny Express, a modern, more streamlined toolkit that accelerates app development while maintaining full flexibility.Alongside Shiny, you’ll dive deep into essential Python data science libraries like Pandas, Seaborn, and Matplotlib. You’ll master how to clean, analyze, visualize, and explore complex datasets with clarity and precision, empowering you to uncover patterns and tell compelling stories with data.This course also introduces PyTorch basics from scratch — perfect for beginners eager to explore deep learning and neural networks. You’ll grasp fundamental machine learning concepts and get hands-on experience building your own models, preparing you to confidently tackle more advanced AI projects.Throughout the course, you’ll engage with practical coding exercises, real-world datasets, and projects focused on creating interactive applications that captivate users and dynamically reveal insights. Whether you aspire to be a data scientist, analyst, or developer, this course will equip you with the skills and confidence to build powerful data-driven applications and understand foundational deep learning techniques in Python.Jump in today and bring your data to life with interactive, intelligent applications!

You’ve just stumbled upon the most complete, in-depth Neural Networks for Regression course online.Whether you want to:- build the skills you need to get your first data science job- move to a more senior software developer position- become a computer scientist mastering in data science- or just learn Neural Networks to be able to create your own projects quickly....this complete Neural Networks for Regression Masterclass is the course you need to do all of this, and more.This course is designed to give you the Neural Network skills you need to become a data science expert. By the end of the course, you will understand the Multilayer Perceptron Neural Networks for Regression method extremely well and be able to apply them in your own data science projects and be productive as a computer scientist and developer.What makes this course a bestseller?Like you, thousands of others were frustrated and fed up with fragmented Youtube tutorials or incomplete or outdated courses which assume you already know a bunch of stuff, as well as thick, college-like textbooks able to send even the most caffeine-fuelled coder to sleep.Like you, they were tired of low-quality lessons, poorly explained topics, and confusing info presented in the wrong way. That’s why so many find success in this complete Neural Networks for Regression course. It’s designed with simplicity and seamless progression in mind through its content.This course assumes no previous data science experience and takes you from absolute beginner core concepts. You will learn the core dimensionality reduction skills and master the Multilayer Perceptron (MLPs) technique. It's a one-stop shop to learn Multilayer Networks. If you want to go beyond the core content you can do so at any time.What if I have questions?As if this course wasn’t complete enough, I

This 200+ day globally recognized, industry-focused bootcamp is your all-in-one training for mastering Artificial Intelligence, Data Science, Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI)  from beginner to expert level with simplicity and depth. Designed for aspiring data scientists, software engineers, AI professionals, and innovation leaders, this course offers a blend of foundational theory, programming practice, machine learning applications, and real-world project. The curriculum aligns with current global AI trends and industry hiring standards.Whether you're targeting top roles in global tech firms, launching an AI-powered startup, or aiming to build a strong data science portfolio this bootcamp ensures you stay ahead in the global AI race.Core Modules (SEO Keywords: Data Science, Python, AI, Machine Learning, Generative AI)Data Science Fundamentals Data Science Sessions Part 1 & 2 – Foundation of modern data science methodologies and approaches.Data Science vs Traditional Analysis – Comparing data science techniques with conventional statistical methods.Data Scientist Journey Parts 1 & 2 – Skills, roles, and global career pathways.Data Science Process Overview – End-to-end project lifecycle and workflows.Programming Essentials (Python & R for Data Science)Introduction to Python for Data Science – Syntax, structures, and data analysis workflows.Python Libraries: Numpy, Pandas, Matplotlib, Seaborn – Building blocks for data processing and visualization.Introduction to R – Fundamentals of R programming for statistics and machine learning.Data Structures and Functions – Hands-on practice in Python & R for real-world data operations.Data Collection & Preprocessing Methods of Data Collection – Surveys, A

Data science is the field that encompasses the various techniques and methods used to extract insights and knowledge from data. Machine learning (ML) and deep learning (DL) are both subsets of data science, and they are often used together to analyze and understand data.In data science, ML algorithms are often used to build predictive models that can make predictions based on historical data. These models can be used for tasks such as classification, regression, and clustering. ML algorithms include linear regression, decision trees, and k-means.DL, on the other hand, is a subset of ML that is based on artificial neural networks with multiple layers, which allows the system to learn and improve through experience. DL is particularly well-suited for tasks such as image recognition, speech recognition, and natural language processing. DL algorithms include convolutional neural networks (CNNs) and recurrent neural networks (RNNs).In a data science project, DL models are often used in combination with other techniques such as feature engineering, data cleaning, and visualization, to extract insights and knowledge from data. For instance, DL models can be used to automatically extract features from images, and then these features can be used in a traditional ML model.In summary, Data science is the field that encompasses various techniques and methods to extract insights and knowledge from data, ML and DL are subsets of data science that are used to analyze and understand data, ML is used to build predictive models and DL is used to model complex patterns and relationships in data. Both ML and DL are often used together in data science projects to extract insights and knowledge from data.IN THIS COURSE YOU WILL LEARN ABOUT :Life Cycle of a Data Science Project.Python libraries like Pandas and Numpy used extensively in Data Science.Matplotlib and Seaborn for Data Visualizatio

Hi there,Welcome to "Generative AI for Data Analysis and Engineering with ChatGPT" course.ChatGPT and AI | Data Analytics and ML Mastering Course with ChatGPT-4o and Next-Gen AI Techniques for Data Analyst Artificial Intelligence (AI) is transforming the way we interact with technology, and mastering AI tools has become essential for anyone looking to stay ahead in the digital age. In today's data-driven world, the ability to analyze data, draw meaningful insights, and apply machine learning algorithms is more crucial than ever. This course is designed to guide you through every step of that journey, from the basics of Exploratory Data Analysis (EDA) to mastering advanced machine learning algorithms, all while leveraging the power of ChatGPT-4o.Machine learning describes systems that make predictions using a model trained on real-world data. For example, let's say we want to build a system that can identify if a cat is in a picture. We first assemble many pictures to train our machine learning model. During this training phase, we feed pictures into the model, along with information about whether they contain a cat. While training, the model learns patterns in the images that are the most closely associated with cats. This model can then use the patterns learned during training to predict whether the new images that it's fed contain a cat.A machine learning course teaches you the technology and concepts behind predictive text, virtual assistants, and artificial intelligence. You can develop the foundational skills you need to advance to building neural networks and creating more complex functions through the Python and R programming languages. We have more data than ever before. But data alone cannot tell us much about the world around us. We need to interpret the information and discover

Welcome to the Full Stack Data Science &amp; Machine Learning Boot Camp Course, the only course you need to learn Foundation skills and get into data science.At over 40+ hours, this Python course is without a doubt the most comprehensive data science and machine learning course available online. Even if you have zero programming experience, this course will take you from beginner to mastery. Here's why:The course is taught by the lead instructor at the PwC, India's leading in-person programming bootcamp.In the course, you'll be learning the latest tools and technologies that are used by data scientists at Google, Amazon, or Netflix.This course doesn't cut any corners, there are beautiful animated explanation videos and real-world projects to build.The curriculum was developed over a period of three years together with industry professionals, researchers and student testing and feedback.To date, I’ve taught over 10000+ students how to code and many have gone on to change their lives by getting jobs in the industry or starting their own tech startup.You'll save yourself over $12,000 by enrolling, but get access to the same teaching materials and learn from the same instructor and curriculum as our in-person programming bootcamp.We'll take you step-by-step through video tutorials and teach you everything you need to know to succeed as a data scientist and machine learning professional.The course includes over 40+ hours of HD video tutorials and builds your programming knowledge while solving real-world problems.In the curriculum, we cover a large number of important data science and machine learning topics, such as:<

This Data Science Course is a comprehensive program designed to provide learners with the essential skills and knowledge needed to understand, analyze, and apply data-driven solutions in the modern world. This course is carefully structured to take you from the basics of data handling to advanced concepts in data analysis, visualization, and predictive modeling.Beginning with fundamental programming skills in Python and R, the course introduces you to core topics such as data cleaning, exploratory data analysis, and statistical methods. From there, you’ll gain hands-on experience with popular tools and libraries, including Pandas, Num Py, Matplotlib, and Scikit-Learn, to manipulate and visualize data effectively. Machine learning concepts are introduced gradually, ensuring a strong foundation in supervised and unsupervised learning, model building, and evaluation techniques.Beyond technical skills, this course emphasizes practical, real-world applications of data science across industries such as business, healthcare, finance, and technology. Through projects and case studies, you will develop the ability to extract actionable insights, solve complex problems, and communicate findings clearly to both technical and non-technical audiences.By the end of the program, you will not only understand the theory but also be confident in applying data science methods to real datasets. Whether you are a student, professional, or aspiring data scientist, the Data Science Course by Shimwa Bonheur equips you with the tools and confidence to thrive in today’s data-driven world.

Programmer en Python pour la Data Science, le Machine Learning, la Data Viz et l'Intelligence Artificielle Ce cours a pour objectif de vous initier à la programmation en Python en lien avec les concepts essentiels du Big Data (Data Science, Machine Learning, IA, etc.). Il ne requiert aucun prérequis et vous permet d'atteindre un niveau solide en seulement 4 heures de formation.Acquérir des bases solides Plus besoin de partir à la chasse aux informations sur Google, l'essentiel de votre apprentissage est concentré dans ce cours.Gagner du temps Ce cours est conçu pour vous familiariser avec la Data Science et Python de manière rapide et efficace. Vous pourrez ainsi atteindre un niveau solide en seulement 4 heures de cours.Une formation qui va à votre rythme Les concepts sont présentés progressivement, à travers des exemples concrets issus de projets d'entreprises et d'universités, vous permettant d'appliquer ce que vous avez appris.Cours récent et régulièrement mis à jour Mis à jour récemment, ce cours est en adéquation avec les compétences actuellement recherchées par les entreprises.Éviter les pièges de débutants Ce cours détaille les bonnes pratiques d'un Data Scientist expérimenté pour rédiger un code de qualité professionnelle.Préparation réussie pour vos examens, certifications et tests techniques sur Python Les exercices inclus dans ce cours constituent un excellent moyen de préparation pour vos examens, certifications et tests techniques en entreprise.Travailler pour les plus grandes entreprises Des entreprises prestigieuses telles qu'Intel, Google, Netflix, Spotify, Meta, mais aussi Renault, la SNCF, Orange, Total, Capgemini, sont actuellement à la recherche de Data Scientists expérimentés maîtrisant Python.Se former à des métiers actuellement recherchés</stron

You want to be able to perform your own data analyses with R? You want to learn how to get business-critical insights out of your data? Or you want to get a job in this amazing field? In all of these cases, you found the right course!We will start with the very Basics of R, like data types and -structures, programming of loops and functions, data im- and export.Then we will dive deeper into data analysis: we will learn how to manipulate data by filtering, aggregating results, reshaping data, set operations, and joining datasets. We will discover different visualisation techniques for presenting complex data. Furthermore find out to present interactive timeseries data, or interactive geospatial data.Advanced data manipulation techniques are covered, e.g. outlier detection, missing data handling, and regular expressions.We will cover all fields of Machine Learning: Regression and Classification techniques, Clustering, Association Rules, Reinforcement Learning, and, possibly most importantly, Deep Learning for Regression, Classification, Convolutional Neural Networks, Autoencoders, Recurrent Neural Networks, ...You will also learn to develop web applications and how to deploy them with R/Shiny.For each field, different algorithms are shown in detail: their core concepts are presented in 101 sessions. Here, you will understand how the algorithm works. Then we implement it together in lab sessions. We develop code, before I encourage you to work on exercise on your own, before you watch my solution examples. With this knowledge you can clearly identify a problem at hand and develop a plan of attack to solve it.You will understand the advantages and disadvantages of d

3.997 / 5.000Aprender a programar en Python no siempre es fácil, especialmente si desea usarlo para la ciencia de datos. De hecho, hay muchas herramientas diferentes que deben aprenderse para poder usar correctamente Python para la ciencia de datos y el aprendizaje automático, y cada una de esas herramientas no siempre es fácil de aprender. Pero, este curso le dará todos los conceptos básicos que necesita sin importar para qué objetivo quiera usarlo, así que si: - Es estudiante y desea mejorar sus habilidades de programación y desea aprender nuevas utilidades sobre cómo usar Python - Necesidad de aprender los conceptos básicos de la ciencia de datos. - Debe comprender las herramientas básicas de ciencia de datos para mejorar su carrera. - Simplemente adquiera las habilidades para uso personal Entonces definitivamente te encantará este curso. No solo aprenderá todas las herramientas que se utilizan para la ciencia de datos, sino que también mejorará su conocimiento de Python y aprenderá a usar esas herramientas para poder visualizar sus proyectos. La estructura del curso Este curso está estructurado de manera que podrá aprender cada herramienta por separado y practicar programando en Python directamente con el uso de esas herramientas. De hecho, al principio aprenderá todas las matemáticas asociadas con la ciencia de datos. Esto significa que tendrá una introducción completa a la mayoría de las funciones y fórmulas estadísticas importantes que existen. También aprenderá a configurar y utilizar Jupyter, así como a escribir su código Python. Después, aprenderá las diferentes bibliotecas de Python que existen y cómo usarlas correctamente. Aquí aprenderás herramientas como Num Py o muchas otras.Finalmente, tendrá una introducción al aprendizaje automático y aprenderá cómo funciona un

Welcome to the Python for Data Science Bootcamp: From Zero to Hero. In this course, we're going to learn how to use Python for Data Science. In this practical course, we'll learn how to collect data, clean data, make visualizations and build a machine learning model using Python.The main goal of this course is to take your programming and analytical skills to the next level to build your career in Data Science. To achieve this goal, we're going to solve hundreds of exercises and many cool projects that will help you put into practice all the programming concepts used in Data Science.We'll learn the top Python Libraries used in Data Science such as Pandas, Numpy and Scikit-Learn and we will use them to learn to solve tasks data scientists&nbsp; deal with on a daily basis (Data Cleaning, Data Visualization, Data Collection and Model Building)This course covers 4 main sections.1. Python for Data Science Crash Course: In the first section, we'll learn all the Python core concepts you need to know for Data Science. We'll learn how to use variables, lists, dictionaries and more.2. Python for Data Analysis: We'll learn Python libraries used for data analysis such as Pandas and Numpy. Both are great tools for exploring and working with data. We'll use Pandas and Numpy to deal with data science tasks such as cleaning and preparing data.3. Python for Data Visualization: In the third section, we'll learn how to make static and interactive visualizations with Pandas. Also, I'll show you some techniques to properly make data visualization.4. Machine Learning with Python: In the fourth section, we'll learn Scikit-Learn by solving a text classification problem in Python. This is the most popular machine learning library in Python and we'll not only learn how to implement machine learning algorithms in Python but also we'll learn the core concepts behind the most common algorithms using practical examples.Bonus (Basic Web Scraping with Python): Remember that at the end o

You’ve just stumbled upon the most complete, in-depth Neural Networks for Classification course online.Whether you want to:- build the skills you need to get your first data science job- move to a more senior software developer position- become a computer scientist mastering in data science- or just learn Neural Networks to be able to create your own projects quickly....this complete Neural Networks for Classification Masterclass is the course you need to do all of this, and more.This course is designed to give you the Neural Network skills you need to become a data science expert. By the end of the course, you will understand the Multilayer Perceptron Neural Networks for Classification method extremely well and be able to apply them in your own data science projects and be productive as a computer scientist and developer.What makes this course a bestseller?Like you, thousands of others were frustrated and fed up with fragmented Youtube tutorials or incomplete or outdated courses which assume you already know a bunch of stuff, as well as thick, college-like textbooks able to send even the most caffeine-fuelled coder to sleep.Like you, they were tired of low-quality lessons, poorly explained topics, and confusing info presented in the wrong way. That’s why so many find success in this complete Neural Networks for Classification course. It’s designed with simplicity and seamless progression in mind through its content.This course assumes no previous data science experience and takes you from absolute beginner core concepts. You will learn the core dimensionality reduction skills and master the Multilayer Perceptron (MLPs) technique. It's a one-stop shop to learn Multilayer Networks. If you want to go beyond the core content you can do so at any time.What if I have questions?As if this course wasn’t com

Welcome to our Data Science and Machine Learning course, meticulously crafted for those passionate about leveraging data and developing sophisticated models. This program starts with the fundamentals of data science, where you'll learn to collect, clean, and analyze data using Python libraries like pandas and Num Py. We’ll cover essential data visualization techniques to transform raw data into meaningful insights that drive decision-making.As you advance, we will delve into a range of machine learning algorithms, including both supervised and unsupervised methods. You'll gain hands-on experience with practical applications such as regression, classification, clustering, and dimensionality reduction. Our approach ensures that you not only understand theoretical concepts but also apply them to real-world scenarios through engaging projects The culmination of the course involves building a stock prediction tool, allowing you to apply your accumulated knowledge to a practical problem. This final project will showcase your ability to develop, implement, and evaluate predictive models, demonstrating your readiness for real-world challenges. By the end of this course, you'll possess a solid foundation in data science and machine learning, equipping you to tackle complex challenges and make valuable contributions in any industry. Join us to unlock your potential and advance your career in this dynamic and rapidly evolving field!

Python est reconnu comme l'un des meilleurs langages de programmation pour sa flexibilité. Il fonctionne dans presque tous les domaines, du développement Web au développement d'applications financières. Cependant, ce n'est un secret pour personne que la meilleure application de Python est dans les tâches de data science, d'analyse de données et de Machine Learning.Bien que Python facilite l'utilisation du Machine Learning et de l'analyse de données, il sera toujours assez frustrant pour quelqu'un qui n'a aucune connaissance du fonctionnement de l'apprentissage automatique.Si vous avez envie d'apprendre l'analyse de données et le Machine Learning avec Python, ce cours est fait pour vous. Ce cours vous aidera à apprendre à créer des programmes qui acceptent la saisie de données et automatisent l'extraction de fonctionnalités, simplifiant ainsi les tâches du monde réel pour les humains.Il existe des centaines de ressources d'apprentissage automatique disponibles sur Internet. Cependant, vous risquez d'apprendre des leçons inutiles si vous ne filtrez pas ce que vous apprenez. Lors de la création de ce cours, nous avons tout filtré pour isoler les bases essentielles dont vous aurez besoin dans votre parcours d'apprentissage en profondeur.C'est un cours de base qui convient aussi bien aux débutants qu'aux experts. Si vous êtes à la recherche d'un cours qui commence par les bases et passe aux sujets avancés, c'est le meilleur cours pour vous.Il enseigne uniquement ce dont vous avez besoin pour vous lancer dans l'apprentissage automatique et l'analyse de données sans fioritures. Bien que cela aide à garder le cours assez concis, il s'agit de tout ce dont vous avez besoin pour commencer avec le sujet.