商业分析专业先修课有哪些?
商业分析的先修课可以分成以下三大类:
第一:数学 (要修过相关课程)
Linear Algebra
Calculus I
Calculus II
Probability and Statistics
第二:计算机 (最好修过课程,如果没有修过课程,通过实践,实习或科研证明掌握能力也是可以的)
Computer programming course in a general programming language such as C, C++, Java, or Python,R
Statistical, econometrics and mathematical applications and tools (for example, SAS, Stata, SQL,MatLab, R, S-Plus, Mathematica).
第三:商科(极少项目作为硬性要求,如有时间最好还是补充一到两门)
Introduction to Corporate Finance
Introduction to Financial Accounting
Introduction to Marketing
当然,没有达到先修课的要求也未必完全申不了,一方面可以积极和学校协商大四补课、或者上网课代替,另一方面也可以用成绩单以外的其他经历来证明自己这些方面的能力。
以下列举几个学校的商业分析硕士项目的先修课要求,供大家参考
1. 女神级别的BA项目:UT项目官网的pre-enrollment criteria中写的要求是“Computer programming experience is required; experience in any programming language is sufficient but Python is preferred (those admitted to the program are strongly encouraged to learn Python prior to beginning the program)”,而没有具体的课程要求。学校在info session中反复强调对quantitative and technical skills的关注,而从录取情况来看,UT也确实偏好那些拥有较强数理背景的申请者。
先修课网课途径:
数学统计课:
Calculus One — Coursera
Linear Algebra - Foundations to Frontiers —Edx
Introduction to Linear Models and Matrix Algebra —Edx
Statistics with R Specialization — Coursera
Introduction to Probability and Data – Coursera
工具及数据库语言:
An Introduction to Interactive Programming in Python - Rice, Coursera
Introduction to Computer Science and Programming Using Python - MIT, edX
R Programming — Coursera
Excel to MySQL: Analytic Techniques for Business Specialization— Coursera
Managing Big Data with MySQL— Coursera
Data Visualization — Coursera
数据挖掘及算法:
Data Science Specialization - 10 courses —John Hopkins— courser
Applied Data Science with Python Specialization – 5 courses - University of Michigan——courser
Mining the Massive Datasets - Stanford, Coursera
Data Mining Specialization — Coursera