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.

Johns Hopkins University
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Analysis, Data Science, Statistics, Mathematical Modeling, Data Modeling, Applied Mathematics
★ 4.4 (800) · Advanced · Specialization · 3 - 6 Months

DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning
★ 4.6 (3.3K) · Intermediate · Specialization · 1 - 3 Months

University of Huddersfield
Skills you'll gain: Data Literacy, Linear Algebra, Graph Theory, Statistical Software, Big Data, Computational Logic, Back-End Web Development, Integral Calculus, Analytics, Matplotlib, Data Visualization, Probability & Statistics, Statistical Programming, Plot (Graphics), Calculus, Scatter Plots, Data Mining, R Programming, Relational Databases, Applied Mathematics
Degree · 1 - 4 Years

University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Plot (Graphics), Statistics, 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
★ 3.6 (16) · Beginner · Specialization · 1 - 3 Months

Imperial College London
Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Unsupervised Learning, Applied Mathematics, Statistical Methods, Descriptive Statistics, Model Optimization, Mathematical Software, Machine Learning Methods, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Geometry, Artificial Neural Networks, Data Science, Data Manipulation
★ 4.6 (15K) · Beginner · Specialization · 3 - 6 Months

Imperial College London
Skills you'll gain: Linear Algebra, Applied Mathematics, Jupyter, Data Science, Data Manipulation, Dimensionality Reduction, Data Transformation, Machine Learning, Computational Thinking
★ 4.6 (13K) · Beginner · Course · 1 - 3 Months

Imperial College London
Skills you'll gain: Dimensionality Reduction, NumPy, Unsupervised Learning, Statistical Methods, Descriptive Statistics, Jupyter, Statistics, Geometry, Linear Algebra, Data Transformation, Python Programming, Advanced Mathematics, Applied Mathematics, Calculus
★ 4 (3.2K) · Intermediate · Course · 1 - 4 Weeks

John Wiley & Sons
Skills you'll gain: Statistical Methods, Exploratory Data Analysis, Data Quality, Statistics, Data Analysis, Data Science, Statistical Analysis, Probability & Statistics, Data Storage, Data Collection, Data Management, Data Pipelines, Statistical Machine Learning, Data-Driven Decision-Making, Probability Distribution, Machine Learning, Linear Algebra
Beginner · Course · 1 - 4 Weeks

Packt
Skills you'll gain: Plotly, PyTorch (Machine Learning Library), NumPy, Matplotlib, Pandas (Python Package), Plot (Graphics), Data Visualization Software, Interactive Data Visualization, Machine Learning Methods, Python Programming, Applied Machine Learning, Scatter Plots, Numerical Analysis, Data Manipulation, Deep Learning, Image Analysis, Linear Algebra, Data Wrangling
Intermediate · Course · 1 - 3 Months

Johns Hopkins University
Skills you'll gain: Calculus, Applied Mathematics, Data Modeling, Model Optimization, Estimation, Graphing, Mathematical Modeling, Data Analysis Software, Algebra, Cost Estimation, Mathematical Software, Linear Algebra, Trigonometry, General Mathematics, Advanced Mathematics, Analysis, Derivatives, Mathematical Theory & Analysis, Geometry, Data Analysis
★ 4.8 (402) · Intermediate · Specialization · 3 - 6 Months

University of Colorado Boulder
Skills you'll gain: Control Systems, Mechanics, Torque (Physics), Simulation and Simulation Software, Linear Algebra, Numerical Analysis, Simulations, Engineering Analysis, Automation Engineering, Differential Equations, Trigonometry, Mathematical Modeling, Engineering Calculations, Applied Mathematics, Engineering, Advanced Mathematics, Algorithms, Physics, Calculus
★ 4.8 (444) · Advanced · Specialization · 3 - 6 Months

University of Colorado Boulder
Skills you'll gain: Integral Calculus, Numerical Analysis, Calculus, Data Science, Applied Mathematics, Linear Algebra, Probability & Statistics, Derivatives
★ 4.6 (111) · Intermediate · Course · 1 - 4 Weeks
Top-rated Data Science courses offered by Imperial College London on Coursera.
Earn a certificate in Data Science from top universities and companies.
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.‎