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: Jupyter, Pandas (Python Package), Programming Principles, Web Scraping, Data Manipulation, Data Structures, NumPy, Python Programming, Computer Programming, Object Oriented Programming (OOP), Web Services, Scripting, Data Analysis Software, Data Analysis, Data Import/Export
Beginner · Course · 1 - 3 Months

Skills you'll gain: Data Storytelling, Data Mining, Big Data, Data Science, Regression Analysis, Data Analysis, Data-Driven Decision-Making, Business Analytics, Business Intelligence, Predictive Analytics, Machine Learning, Deep Learning
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Data Storytelling, Data Ethics, Data Analysis, Data-Driven Decision-Making, Analytics, Workflow Management, Business Analytics, Data Science, Advanced Analytics, Business Workflow Analysis, Project Management, Communication, Stakeholder Communications, Data Management, Professional Networking
Advanced · Course · 1 - 3 Months

IBM
Skills you'll gain: Data Storytelling, Dashboard, Model Evaluation, Data Visualization Software, Data Wrangling, Data Visualization, Web Scraping, Supervised Learning, Data Modeling, Unsupervised Learning, SQL, Exploratory Data Analysis, Matplotlib, Pandas (Python Package), Plotly, Data Analysis, Predictive Modeling, Jupyter, Professional Networking, Generative AI
Build toward a degree
Beginner · Professional Certificate · 3 - 6 Months

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

DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Exploratory Data Analysis, Statistical Hypothesis Testing, Sampling (Statistics), Probability & Statistics, Linear Algebra, Bayesian Statistics, Probability Distribution, Statistical Machine Learning, Data Science, Probability, NumPy, Applied Mathematics, Dimensionality Reduction, Data Transformation, Calculus, Numerical Analysis, Machine Learning Algorithms, Machine Learning, Data Manipulation
Intermediate · Specialization · 1 - 3 Months

Skills you'll gain: Dashboard, Web Scraping, Pandas (Python Package), Data Presentation, Data Visualization, Data Analysis, Data Processing, Data Science, Python Programming, Data Manipulation, Jupyter, Data Collection
Intermediate · Course · 1 - 4 Weeks
Johns Hopkins University
Skills you'll gain: Shiny (R Package), Exploratory Data Analysis, Model Evaluation, Regression Analysis, Statistical Analysis, R Programming, Data Manipulation, Data Presentation, Data Cleansing, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Machine Learning Algorithms, Plot (Graphics), Probability & Statistics, Rmarkdown, Statistical Programming, Data Science, Machine Learning, GitHub
Beginner · Specialization · 3 - 6 Months

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

Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Model Evaluation, Data Analysis, Predictive Modeling, Data Pipelines, Data Import/Export, Regression Analysis, Data Science, Pandas (Python Package), Data Manipulation, Predictive Analytics, Data Cleansing, Statistical Analysis, Scikit Learn (Machine Learning Library), Data Preprocessing, Matplotlib, Data Visualization, Scatter Plots, Python Programming
Intermediate · Course · 1 - 3 Months

Skills you'll gain: Data Storytelling, Model Evaluation, Data Modeling, SQL, Model Deployment, Data Mining, Jupyter, Databases, Data Cleansing, Business Research, Data Preprocessing, Data Science, Relational Databases, Business Analysis, Data Analysis, IBM Cloud, Data Visualization Software, R (Software), Big Data, Python Programming
Build toward a degree
Beginner · Specialization · 3 - 6 Months
University of Michigan
Skills you'll gain: Pandas (Python Package), Statistical Analysis, Data Manipulation, Data Cleansing, Data Analysis, Probability & Statistics, Sampling (Statistics), NumPy, Pivot Tables And Charts, Statistical Hypothesis Testing, Jupyter, Python Programming, Data Import/Export, Programming Principles
Intermediate · 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.