IBM - Data Science Fundamentals with Python and SQL Specialization
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Data Science Fundamentals with Python and SQL Specialization at Coursera Overview
Duration | 5 months |
Start from | Start Now |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Beginner |
Official Website | Go to Website  |
Credential | Certificate |
Data Science Fundamentals with Python and SQL Specialization at Coursera Highlights
- 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
Data Science Fundamentals with Python and SQL Specialization at Coursera Course details
- Data science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater. This Specialization from IBM will help anyone interested in pursuing a career in data science by teaching them fundamental skills to get started in this in-demand field.
- The specialization consists of 4 self-paced online courses that will provide you with the foundational skills required for Data Science, including open source tools and libraries, Python, Statistical Analysis, SQL, and relational databases. You?ll learn these data science pre-requisites through hands-on practice using real data science tools and real-world data sets.
Data Science Fundamentals with Python and SQL Specialization at Coursera Curriculum
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 and AI
This course will take you from zero to programming in Python in a matter of hours?no prior programming experience necessary! You will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills
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.
Databases and SQL for Data Science
The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.
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