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.

Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Application Programming Interface (API), Automation, Data Analysis
Beginner · Course · 1 - 3 Months

IBM
Skills you'll gain: Exploratory Data Analysis, Dashboard, Data Visualization Software, Data Visualization, Model Evaluation, SQL, Unsupervised Learning, Interactive Data Visualization, Data Transformation, Supervised Learning, Jupyter, Data Analysis, Data Cleansing, Data Manipulation, Data Literacy, Plotly, Data Mining, Generative AI, Professional Networking, Data Import/Export
Build toward a degree
Beginner · Professional Certificate · 3 - 6 Months

Skills you'll gain: Data Literacy, Data Mining, Big Data, Cloud Computing, Data Analysis, Data Science, Digital Transformation, Data-Driven Decision-Making, Deep Learning, Machine Learning, Artificial Intelligence
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: SQL, Relational Databases, Stored Procedure, Databases, Query Languages, Jupyter, Data Manipulation, Data Analysis, Pandas (Python Package), Transaction Processing, Python Programming
Beginner · Course · 1 - 3 Months

Skills you'll gain: SQL, Jupyter, Data Literacy, Data Mining, Data Modeling, Relational Databases, Stored Procedure, Model Deployment, Databases, Data Science, Big Data, Computer Programming Tools, Query Languages, Data Visualization Software, GitHub, Data Preprocessing, Data Cleansing, R (Software), Cloud Computing, Python Programming
Build toward a degree
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
Skills you'll gain: Shiny (R Package), Rmarkdown, Exploratory Data Analysis, Model Evaluation, Regression Analysis, Version Control, Statistical Analysis, R Programming, Data Manipulation, Data Cleansing, Data Science, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Machine Learning Algorithms, Plotly, Plot (Graphics), Interactive Data Visualization, Machine Learning, GitHub
Beginner · Specialization · 3 - 6 Months

Multiple educators
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Literacy, Data Mining, Pandas (Python Package), Data Presentation, Correlation Analysis, Web Scraping, NumPy, Data Import/Export, Probability & Statistics, Programming Principles, Predictive Modeling, Computer Programming Tools, Data Science, Unsupervised Learning, Machine Learning, Project Management
Beginner · Specialization · 3 - 6 Months

University of California, Davis
Skills you'll gain: Data Governance, SQL, Data Management, Data Quality, Database Design, Query Languages, Data Literacy, Data Manipulation, Data Modeling, Relational Databases, Data Science, Databases, Data Analysis, Data Transformation
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Presentation, Statistics, Data Visualization, Relational Databases, Stored Procedure, Data Import/Export, Data Science, Programming Principles, Computer Programming Tools, Web Scraping, Data Visualization Software, Python Programming
Build toward a degree
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Data Storytelling, Rmarkdown, Data Literacy, Data Visualization, Data Presentation, Data Ethics, Data Cleansing, Data Validation, Ggplot2, Tableau Software, Sampling (Statistics), Presentations, Spreadsheet Software, Data Analysis, Stakeholder Communications, LinkedIn, Data Structures, Object Oriented Programming (OOP), Interviewing Skills, Applicant Tracking Systems
Build toward a degree
Beginner · Professional Certificate · 3 - 6 Months

University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning
Build toward a degree
Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Jupyter, Data Modeling, Model Deployment, Data Science, Data Preprocessing, Data Cleansing, Data Mining, Model Evaluation, Business Analysis, Data Analysis, Business Requirements, Decision Tree Learning, Data Storytelling
Beginner · Course · 1 - 4 Weeks
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.