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商業(yè)分析到底需要哪些先修課,看看美國學(xué)校怎么說

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Conditional Courses

The following sets of courses in math, R, Python and SQL are representative of the kind of programming background that we envision all our students to possess.  Please complete these courses and send your certificate or proof of completion to Kip Powers no later than June 1, 2019.  If you prefer to take some of these classes in person (as opposed to online), please send the syllabus of the course you would like to take to Allison Jacobs for approval.  

// Math Courses: Coursera

Skill Track

Hours

Link

Mathematics for Machine Learning: Multivariate Calculus

10-20

https://www.coursera.org/learn/multivariate-calculus-machine-learning

Mathematics for Machine Learning:  Linear Algebra

10-20

https://www.coursera.org/learn/linear-algebra-machine-learning

// R Programming, Datacamp

Skill Track

Hours

Link

R Programming (4 Courses)

18

https://www.datacamp.com/tracks/r-programming

Importing and Cleaning Data (4 Courses)

14

https://www.datacamp.com/tracks/importing-cleaning-data-with-r

Data Manipulation (4 courses)

16

https://www.datacamp.com/tracks/data-manipulation-with-r

Statistics with R (4 Courses)

16

https://www.datacamp.com/tracks/statistics-with-r

//Python Programming, Datacamp

Skill Track

Hours

Link

Python Programming (4 Courses)

15

https://www.datacamp.com/tracks/python-programming

Importing and Cleaning Data (4 Courses)

14

https://www.datacamp.com/tracks/importing-cleaning-data-with-python

Data Manipulation (4 courses)

16

https://www.datacamp.com/tracks/data-manipulation-with-python

//SQL, edX

Course Name

Hours

Link

Querying Data with Transact-SQL

25-30

https://www.edx.org/course/querying-data-transact-sql-microsoft-dat201x-0

Overall computing course-Recommended, Not required

While programming itself is simply a means to analytics, we find that sometimes students are proficient in programming but may not have an adequate understanding of the general computing environment – particularly if they have not undergone formal training in computer science.

The following course might help add to that understanding through a basic introduction to principles of computing and algorithmic thinking.

This Specialization covers much of the material that first-year Computer Science students take at Rice University. Students learn sophisticated programming skills in Python from the ground up and apply these skills in building more than 20 fun projects.

Course Name

Hours

Link

Fundamentals of Computing Specialization

200+

https://www.coursera.org/specializations/computer-fundamentals

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