关于此课程： Much of the world's data resides in databases. SQL (or Structured Query Language) is a powerful language which is used for communicating with and extracting data from databases. A working knowledge of databases and SQL is a must if you want to become a data scientist. The purpose of this course is to introduce relational database concepts and help you learn and apply knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment. The emphasis in this course is on hands-on and practical learning . As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python. No prior knowledge of databases, SQL, Python, or programming is required. Anyone can audit this course at no-charge. If you choose to take this course and earn the Coursera course certificate, you can also earn an IBM digital badge upon successful completion of the course. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.
此课程适用人群： This course is designed for anyone interested in learning SQL, especially those who want to apply SQL for data science. Therefore it is ideal for those aspiring to become data scientists. It is also suitable for those who want to become data analysts, data engineers, database administrators, or a database developers. This course is for beginners in SQL and Data Science. It does not require any prior knowledge of SQL, databases, Python, or programming.
教学方： Rav Ahuja, Data Science Program Manager
IBM
| 基本信息 | |
| 级别 | 初级 |
| 承诺学习时间 | 3-4 weeks of study, 2-4 hours/week. |
| 语言 | English |
| 硬件要求 | Only browser access is required. Access to cloud based environment will be provided for hands-on labs. |
| 如何通过 | 通过所有计分作业以完成课程。 |
| 用户评分 |
- 视频: Introduction to Databases
- 视频: How to create a Database instance on Cloud?
- Reading: Hands-on LAB: Provision a Cloud hosted Database instance
- LTI Item: OPTIONAL: Applying IBM Cloud Promo Code
- 视频: CREATE Table Statement
- 视频: SELECT Statement
- Reading: Count, Distinct, Limit
- 视频: INSERT Statement
- 视频: UPDATE and DELETE Statements
- Reading: Hands-on LAB: Composing and Running basic SQL queries
- Reading: About this Optional lesson
- 视频: Information and Data Models
- 视频: Types of Relationships
- 视频: Mapping Entities to Tables
- 视频: Relational Model Concepts
- Reading: Additional Reading
- Practice Quiz: Practice Quiz: Review of Relational Database Concepts
- Practice Quiz: Optional Not Graded Quiz on Relational Concepts
- 视频: Sorting Result Sets
- 视频: Grouping Result Sets
- Reading: Hands-on LAB: String Patterns, Sorting & Grouping
- 视频: Join Overview
- 视频: Inner Join
- 视频: Left Outer Join
- 视频: Right Outer Join
- 视频: Full Outer Join
- Reading: Hands-on LAB: JOINs
- Reading: About this Optional lesson
- 视频: Relational Model Constraints
- 视频: Relational Model Constraints - Advanced
- Reading: Additional Information on Keys and Constraints
- Practice Quiz: Practice Quiz: Review of Database Constraints
- Practice Quiz: Optional Not Graded Quiz on Constraints
- 视频: Writing code using DB-API
- 视频: Connecting to a database using ibm_db API
- LTI Item: Hands-on LAB 1: Connecting to a database instance
- 视频: Creating tables, loading data and querying data
- LTI Item: Hands-on LAB 2: Creating tables, inserting and querying Data
- LTI Item: Hands-on Tutorial: Accessing databases with SQL magic
- 视频: Analyzing data with Python
- LTI Item: Hands-on LAB 3: Analyzing a real world data set
- Reading: Working with real-world data sets
- Reading: Built-in Functions, Dates, Timestamps
- LTI Item: Hands-on Lab 1: Querying real world datasets
- LTI Item: Jupyter notebook with problems for Peer Reviewed Assignment
- Reading: IBM Digital Badge
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A great course about SQL and Databases but the final assignment should have been about writing python code to access database and analyze data, as shown in one of the videos where a pandas dataframe was created. Instead, the assignment made us write SQL code inside Jupyter Notebook. That was not needed at least as far as I am concerned. If we had to write SQL, we could have just done it on IBM Db2 Cloud.
Superb Content. Extremely satisfied with this course
Well structured
MR
Covers all basics of SQL and methods of accessing of SQL with Python.