Spécialisation Data Science Fundamentals with Python and SQL
Build the Foundation for your Data Science career. Develop hands-on experience with Jupyter, Python, SQL. Perform Statistical Analysis on real data sets.
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Ce que vous allez apprendre
Working knowledge of Data Science Tools such as Jupyter Notebooks, R Studio, GitHub, Watson Studio
Python programming basics including data structures, logic, working with files, invoking APIs, and libraries such as Pandas and Numpy
Statistical Analysis techniques including Descriptive Statistics, Data Visualization, Probability Distribution, Hypothesis Testing and Regression
Relational Database fundamentals including SQL query language, Select statements, sorting & filtering, database functions, accessing multiple tables
Compétences que vous acquerrez
À propos de ce Spécialisation
Projet d'apprentissage appliqué
All courses in the specialization contain multiple hands-on labs and assignments to help you gain practical experience and skills with a variety of data sets.The projects range from building a dashboard with Python, analyzing socio-economic data with SQL, and performing regression analysis with housing data.
Just basic computer literacy and willingness to self-learn online. No prior knowledge of computer science or programming languages required.
Just basic computer literacy and willingness to self-learn online. No prior knowledge of computer science or programming languages required.
Cette Spécialisation compte 5 cours
Tools for Data Science
What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
Python for Data Science, AI & Development
Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
Python Project for Data Science
This mini-course is intended to for you to demonstrate foundational Python skills for working with data. The completion of this course involves working on a hands-on project where you will develop a simple dashboard using Python.
Statistics for Data Science with Python
This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis. You will take a hands-on approach to statistical analysis using Python and Jupyter Notebooks – the tools of choice for Data Scientists and Data Analysts.
Offert par

IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Foire Aux Questions
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
Can I just enroll in a single course?
Puis-je m'inscrire à un seul cours ?
Can I take the course for free?
Puis-je suivre le cours gratuitement ?
Ce cours est-il vraiment accessible en ligne à 100 % ? Dois-je assister à certaines activités en personne ?
Quelle est la durée nécessaire pour terminer la Spécialisation ?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
Puis-je obtenir des crédits universitaires si je réussis la Spécialisation ?
¿Necesito realizar los cursos en un orden específico?
¿Obtendré créditos universitarios por completar la Especialización?
D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.