The complete SQL & Python for SQL with Hands-on Questions
What you'll learn
- All fundamental SQLs for everyone
- Complete Intermediate SQLs for job seekers
- Advanced SQLs for experienced learners
- More than 300 practical questions related to SQLs and Python
- How to utilize and manage PostgreSQL and Pgadmin interfaces to write SQLs
- Efficient Database administration
- How to solve real world & capstone projects about SQLs and Python
- Store procedures, triggers, regular expressions and statistical analysis with PostgreSQL & Python
- Business analysis methods and backgrounds such as cohort analysis, credit risk analysis, retail recommendation system, fraud detection and stock trend analysis
- How to work with Python, SQLs and external files together
- Comprehensive job interview guidance on SQLs and Python
Requirements
- Able to use computer including being able to install software
- Prior exposure to programming languages will be helpful
Description
In this more than 16 hours course, we would teach the complete PostgreSQL Database, SQL, and Python for starting the career in data science! Please note, this is a really “for everyone’s” course.
You must take this course, not only because SQL and Python are so far the most useful tools for data analysis in the world, but also because you are learning a real hands-on as well as theoretical course about how to apply SQL and Python into practice! After you have solved and digested all those 300 practical questions, you will definitely become a real SQL & Python expert!
This is so far the most comprehensive guide to learn PostgreSQL database, PgAdmin management, all levels SQL commands and Python programming for SQL and database connections. One of most important features of this course is that it is a question proposition and solution based – we are trying to take a hands-on approach to tackle each practical problem while providing you a systematic explanation on theories.
This is also a business and data analytics jobs based course, as we have designed several real world and job interview projects for different levels’ students. We are not only proposing these questions and projects but also providing you with complete solution codes in SQL and Python
Upon completing this course, you’ll be able to apply SQL and Python to solve various data science, machine learning, statistical analysis and business problems under different environments and interfaces.
Want to be successful? Then join this course! You’ll learn by doing and meet various challenges!
Who this course is for:
- Anyone who desires to learn SQL, PostgreSQL, Pgadmin, Anaconda, Spyder, Python and Data Science
- Anyone who wishes to learn basic knowledge and skills statistics
- Anyone who needs to get started data analysis or science career using Database, SQLs and Python
- Anyone who wants to learn how to apply SQLs and Python into various business and industry areas
- Anyone who needs to expend and improve knowledge and skill set in Python, SQLs and PostgreSQL database administration
Instructor
- 4.1 Instructor Rating
- 1,999 Reviews
- 18,445 Students
- 3 Courses
Having successfully led the development of cutting-edge risk models using Big data at multiple major financial institutions and excelled in the advanced analytics field for the past 15 years, I am very enthusiastic at transferring knowledge and skills to the job seekers and new comers in the field of data analytics and application to business.
I hold a PhD in Statistics and operational research. I am also a passionate educator, teaching as a principal instructor of a Toronto-based college, including advanced SAS data mining, Python & R for data science and machine learning and Big data analytics foundation and projects and for over 10 years. As a result, I have helped many of my students land their dream jobs in advanced analytics.
I am also a Big data experts in machine learning, predictive modelling and retail/marketing analytics in Canada. My work includes but not limited to: implementation of Big data analysis for credit bureau, model vetting and validation for banking capital market, and customers attrition and life stage/life style segmentation for retail banks as well as big market firms. I also worked closely with senior executives and Big data architects in the field of health science to provide strategic advice.