# 查看完整版本 : 求救：大學數elective 選讀Numerical analysis 定 stochastic processes ?

22point 2019-12-31 05:58 PM

## 求救：大學數elective 選讀Numerical analysis 定 stochastic processes ?

IWC-Rolex 2019-12-31 08:24 PM

narius 2020-1-1 12:32 AM

It also depends on the actual materials. Just a title tells us nothing.

Plus, undergraduate classes really do not really do much aside from giving you the basic ideas, may be with a little practice.

So flip a coin.

22point 2020-1-1 05:56 AM

Stochastic Processes I
Random vectors, multivariate densities, covariance matrix, multivariate normal distribution. Random walk, Poisson process. Other topics if time permits.

Stochastic Processes II
Markov chains in discrete and continuous time, random walk, recurrent events. If time permits, topics chosen from stationary normal processes, branching processes, queuing theory.

Introduction to Numerical Analysis: Linear Algebra
Analysis of numerical methods for linear algebraic systems and least squares problems. Orthogonalization methods. Ill conditioned problems. Eigenvalue and singular value computations. Knowledge of programming recommended

Introduction to Numerical Analysis: Approximation and Nonlinear Equations
Rounding and discretization errors. Calculation of roots of polynomials and nonlinear equations. Interpolation. Approximation of functions. Knowledge of programming recommended.

narius 2020-1-1 11:07 AM

Well .. since numerical method is basically linear algebra in that context .. take that first. You will need it no matter what you do (assuming you need more).

Approximation to nonlinear equations is very situational. Very simple method (like just a simple discretization with a grid) works if you have enough computational power to brute force it.

A lot of the stuff done in stochastic modeling needs linear algebra anyway. To be fair, it depends a bit on the instructor. Take markov chain as an example. It is one approach to just show you all the math and proofs. It is quite another to show how you apply the concept in an application. Although I guess if it is taught out of a math department, it would be on the abstract side.

What do you want to do career-wise? If you want a STEM career, this decision is kind of moot since you will need an advance degree anyway.

22point 2020-1-1 11:25 AM

I think I would like to be a financial analyst or data analyst

IWC-Rolex 2020-1-1 12:16 PM

[quote]原帖由 [i]22point[/i] 於 2020-1-1 11:25 AM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512479381&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]
I think I would like to be a financial analyst or data analyst [/quote]

22point 2020-1-1 12:20 PM

[quote]原帖由 [i]IWC-Rolex[/i] 於 2020-1-1 12:16 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512481286&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

Thank you ,ching.畢竟GPA反映一個人醒唔醒

le123 2020-1-1 09:28 PM

Stochastic processes for sure, if u learn more financial maths, those calculation must involve time factor. Stochastic process provide u basic idea on handling time factor. If ur calculus and alegbra good enough, u can handle numerical analysis.

22point 2020-1-2 06:44 AM

[quote]原帖由 [i]le123[/i] 於 2020-1-1 09:28 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512503896&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]
Stochastic processes for sure, if u learn more financial maths, those calculation must involve time factor. Stochastic process provide u basic idea on handling time factor. If ur calculus and alegbra  ... [/quote]
Thank you ching. 但係我直接揀Math of finance 呢個course 會唔會更好定stochastic processes? 呢到係content
The Mathematics of Finance course:
Introduction to the mathematics of financial models. Basic probabilistic models and associated mathematical machinery will be discussed, with emphasis on discrete time models. Concepts covered will include conditional expectation, martingales, optimal stopping, arbitrage pricing, hedging, European and American options.

[quote]原帖由 [i]22point[/i] 於 2020-1-2 06:44 AM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512516849&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

Thank you ching. 但係我直接揀Math of finance 呢個course 會唔會更好定stochastic processes? 呢到係content
The Mathematics of Finance course:
Introduction to the mathematics of financial models. Basic probabilistic mod ... [/quote]

22point 2020-1-2 12:59 PM

[quote]原帖由 [i]竹劍[/i] 於 2020-1-2 07:22 AM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512517326&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

narius 2020-1-2 02:21 PM

[quote]原帖由 [i]竹劍[/i] 於 2020-1-2 07:22 AM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512517326&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

Sigh .. i wish students care a little more about actual learning, than just a grade. But i do understand why people are so obsessed with KPIs.

If you go interview for a data science job (and at least in the US), they give you actual problem to solve. Having a high GPA does not necessarily contributes to that, particularly if you are in large classes where the instructor is too lazy to do anything but multiple-choice exams.

le123 2020-1-2 02:43 PM

[quote]原帖由 [i]22point[/i] 於 2020-1-2 06:44 AM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512516849&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

Thank you ching. 但係我直接揀Math of finance 呢個course 會唔會更好定stochastic processes? 呢到係content
The Mathematics of Finance course:
Introduction to the mathematics of financial models. Basic probabilistic mod ... [/quote]

22point 2020-1-2 02:53 PM

[quote]原帖由 [i]le123[/i] 於 2020-1-2 02:43 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512534430&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

le123 2020-1-2 03:38 PM

[quote]原帖由 [i]22point[/i] 於 2020-1-2 02:53 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512534839&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

IWC-Rolex 2020-1-2 04:51 PM

[quote]原帖由 [i]22point[/i] 於 2020-1-2 02:53 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512534839&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

Master的話，值得讀既Master唔會太多。

[quote]原帖由 [i]22point[/i] 於 2020-1-2 02:53 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512534839&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

[[i] 本帖最後由 竹劍 於 2020-1-2 11:23 PM 編輯 [/i]]

22point 2020-1-3 02:21 PM

elective 數係冇用嘅。。。

[quote]原帖由 [i]22point[/i] 於 2020-1-3 02:21 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512575902&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

22point 2020-1-4 07:49 PM

[quote]原帖由 [i]竹劍[/i] 於 2020-1-3 05:14 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512583398&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

[quote]原帖由 [i]22point[/i] 於 2020-1-4 07:49 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512629091&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

narius 2020-1-4 10:08 PM

[quote]原帖由 [i]22point[/i] 於 2020-1-4 07:49 PM 發表 [url=https://www.discuss.com.hk/redirect.php?goto=findpost&pid=512629091&ptid=28790458][img]https://www.discuss.com.hk/images/common/back.gif[/img][/url]

Ok .. here is a very brief run down on the different "type" of data science.

Data science (or something called analytics, data analytics, or business analytics) programs can be run out of a CS department, or the IS side of a business school, or even an econ department. Because it is hot, everyone is jumping into the game.

Obviously each program varies ... but roughly speaking:

1) CS data science programs focuses more on the technology and "data plumbing".
2) B-school type programs focuses more on applications. The techniques can be exactly the same thing.
3) Sometimes econ department will market econometrics as data science (not completely unreasonable) .. and basically is stat modeling with econ reasoning.

So if you want to focus on the advancement of the tech, go for a CS program. If you are more apply, go for a business school program.

From my experiences (this includes both research and consulting on data science issues), just the techniques and understanding of them are not quite enough to be good in a business data science team. Typically you also need some domain knowledge. A simple example is clustering (in fact, i just had this discussion with a data scientist of a silicon valley company yesterday). Without business domain knowledge (i am talking about technical modeling of business processes, not just some "soft" knowledge of your business), it is very hard to formulate a reasonable distance measure for the clustering. The exercise always has to tie back to the final business objective. But *only* knowing the business is also not enough. For example, in this case one needs to be able to reason about math structures in high dimension.