Les cours en data science peuvent vous aider à comprendre comment analyser des données, créer des modèles et évaluer leurs performances. Vous pouvez développer des compétences en statistique, apprentissage automatique, préparation des données et visualisation. De nombreux cours utilisent des langages et bibliothèques courants pour travailler sur des projets pratiques.

Coursera
Skills you'll gain: Applied Machine Learning, Predictive Modeling, Jupyter, Predictive Analytics, Model Evaluation, Model Optimization, Data Analysis, Machine Learning, Data Science, Python Programming
★ 4.7 (228) · Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: PyTorch (Machine Learning Library), Model Training, Convolutional Neural Networks, Transfer Learning, Image Analysis, Predictive Modeling, Deep Learning, Radiology, Medical Imaging, Machine Learning, Computer Vision, Data Preprocessing, Data Transformation
★ 4.5 (340) · Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Data Manipulation, Analysis
★ 4.5 (393) · Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Amazon S3, Amazon Web Services, Cloud Hosting, Cloud Storage, Version Control, Encryption, Data Storage, Cloud Security
★ 4.5 (1.3K) · Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Microsoft Excel, Excel Formulas, Pivot Tables And Charts, Data Analysis, Data Manipulation, Microsoft Office, Data Mining
★ 4.7 (4.8K) · Intermediate · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Google Analytics, Web Analytics and SEO, Statistical Reporting, Data-Driven Marketing, Analytics, Data Analysis, User Accounts
★ 4.4 (1.5K) · Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Portfolio Risk, Investment Management, Risk Management, Financial Analysis, Financial Management, Risk Modeling, Risk Analysis, Portfolio Management, Financial Market, Investments, Statistics
★ 4.3 (2.2K) · Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Model Deployment, Decision Tree Learning, Applied Machine Learning, Predictive Modeling, Machine Learning Software, Microsoft Azure, No-Code Development, Machine Learning, Data Preprocessing, Predictive Analytics, Model Training, Cloud Deployment, Feature Engineering, Machine Learning Algorithms, Model Evaluation, Data Science, Data Analysis, Classification Algorithms
★ 4.5 (834) · Beginner · Guided Project · Less Than 2 Hours

Coursera
Skills you'll gain: Statistical Reporting, Data Visualization, Big Data, SQL, Interactive Data Visualization, Query Languages, Data Import/Export, Google Cloud Platform, Data Warehousing, Data Sharing, Analytics
★ 4.3 (277) · Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Fine-tuning, Tensorflow, Keras (Neural Network Library), Model Training, Model Evaluation, Transfer Learning, Natural Language Processing, Data Preprocessing, Deep Learning, Data Pipelines
★ 4.6 (212) · Intermediate · Guided Project · Less Than 2 Hours

Skills you'll gain: Google Sheets, Data Visualization, Spreadsheet Software, Data Presentation, Plot (Graphics), Statistical Visualization, Data Analysis, Business Analytics, Descriptive Analytics, Productivity Software, Business Analysis, Data Manipulation, Google Workspace, Analytics, Descriptive Statistics, Statistics, Data Cleansing
★ 4.3 (1.1K) · Beginner · Guided Project · Less Than 2 Hours

Skills you'll gain: Technical Analysis, Google Sheets, Spreadsheet Software, Market Data, Cloud Computing, Data Visualization, Trend Analysis
★ 4.2 (303) · Beginner · Guided Project · Less Than 2 Hours
High-quality free Data Science courses you can start today.
Top-rated Data Science courses offered by Coursera on Coursera.
Top-rated beginner-friendly Data Science courses with no prerequisites.
Quick Data Science courses you can complete in a few hours or less.
Data science is an interdisciplinary field that combines statistics, computer science, and domain expertise to extract meaningful insights from data. It plays a crucial role in decision-making across various industries, helping organizations to understand trends, predict outcomes, and optimize processes. In today's data-driven world, the ability to analyze and interpret data is essential for businesses to remain competitive and innovative.‎
A career in data science can lead to various roles, including data analyst, data engineer, machine learning engineer, and data scientist. These positions are in high demand across sectors such as finance, healthcare, technology, and marketing. Each role focuses on different aspects of data, from data collection and cleaning to advanced analytics and predictive modeling, offering diverse opportunities for professionals.‎
To pursue a career in data science, you should develop a strong foundation in several key skills. These include programming languages like Python and R, statistical analysis, data visualization, and machine learning. Familiarity with databases and tools such as SQL and Tableau is also beneficial. Additionally, soft skills like problem-solving, critical thinking, and effective communication are essential for translating data insights into actionable strategies.‎
There are numerous online courses available for learning data science. Some of the best options include the IBM Data Science Professional Certificate, which covers essential skills and tools, and the Applied Data Science Specialization, which focuses on practical applications. These courses provide a structured learning path and hands-on experience to help you build your data science expertise.‎
Yes. You can start learning data science on Coursera for free in two ways:
If you want to keep learning, earn a certificate in data science, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
To learn data science effectively, start by identifying your learning goals and the specific skills you want to acquire. Begin with foundational courses that cover basic concepts and gradually progress to more advanced topics. Engage in hands-on projects to apply your knowledge, and consider joining online communities or study groups to enhance your learning experience. Consistent practice and real-world application are key to mastering data science.‎
Data science courses typically cover a range of topics, including data manipulation, statistical analysis, machine learning, data visualization, and big data technologies. You may also encounter specialized subjects such as natural language processing, data ethics, and data engineering. This comprehensive curriculum prepares you to tackle various challenges in the field and equips you with the skills needed to analyze complex datasets.‎
For training and upskilling employees in data science, programs like the CertNexus Certified Data Science Practitioner Professional Certificate and the Fractal Data Science Professional Certificate are excellent choices. These courses are designed to enhance practical skills and provide a solid foundation in data science, making them suitable for workforce development.‎