This course has a singular and clear aim, to empower you to do statistical tests, ready for incorporation into your dissertations, research papers, and presentations. The ability to summarize data, create plots and charts, and to do the tests that you commonly see in the literature is a powerful skill indeed. Not only will it further your career, but it will put you in the position to contribute to the advancement of humanity through scientific research.
Doing Clinical Research: Biostatistics with the Wolfram Language
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Doing Clinical Research: Biostatistics with the Wolfram Language
Universidade da Cidade do Cabo
Informações sobre o curso
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Habilidades que você terá
Learn to use the Wolfram Language to summarize data and create plotsLearn to use the Wolfram Language to do common statistical tests
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Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível iniciante
Aprox. 10 horas para completar
Sugerido: Four weeks of study, at approximately five hours per week.
Inglês
Legendas: Inglês
Programa - O que você aprenderá com este curso
2 horas para concluir
Week 1
This first week establishes the aims of the course and motivation for using the Wolfram Language. We aim to support you in gaining a remarkable new set of skills for doing statistical analysis that you can continue to use long after you complete the course. We will also describe the process of procuring the software that you will use in the course. The first is the absolutely free version, which is software as a service, meaning it runs in any web browser. The second is the desktop version. If you work or study at an institution with a site licence, you will be able to get the software for free. There is also the option to purchase your own licence.
2 horas para concluir
14 vídeos (Total 54 mín.), 8 leituras
14 videos
Welcome6min
The Klopper Research Group1min
Assumptions1min
Learning a computer language1min
Why the Wolfram language?7min
Getting Mathematica5min
The new Wolfram Cloud1min
The Wolfram Cloud1min
The Wolfram Programming Lab8min
Free-form input and Wolfram Alpha in the Cloud3min
Mathematica27s
Free-form input and Wolfram Alpha in the desktop7min
Help and documentation3min
Assignment notebooks4min
8 leituras
How this Course Works10min
Welcome to Module 110min
Meet the Course Instructor10min
Module 1 Notebook10min
Welcome to Wolfram Cloud10min
Welcome to Module 310min
Module 3 Notebook10min
Module 3 Exercise10min
3 horas para concluir
Week 2
In week 2, we start with some actual coding, now that you know about the Wolfram Language and its different coding environments. We start off with a demonstration of a completed project. It is just a little teaser, showcasing what you will be able to do at the end. Next, we are going to learn to code by doing simple arithmetic. That is simple addition, subtraction, multiplication, and so on. Once you have realized just how simple these tasks are, you will be introduced to the way in which data is stored in a computer language. These are the stepping stone required to bringing in your own data, ready for the analyses in the following weeks.
3 horas para concluir
20 vídeos (Total 100 mín.), 8 leituras, 1 teste
20 videos
Simulated data demonstration - part 11min
Simulated data demonstration - part 27min
Simple arithmetic30s
Addition and subtraction5min
Multiplication and division9min
Powers5min
Arithmetical order2min
Calculating a mean5min
Working with data40s
Lists part 17min
Lists part 23min
Tables7min
Index10min
Datasets9min
Selecting6min
Dataset functions3min
Creating lists from datasets2min
Spreadsheets6min
Spreadsheets in the cloud4min
8 leituras
Welcome to Module 410min
Module 4 Notebook10min
Welcome to Module 510min
Module 5 Exercise10min
Welcome to Module 610min
Module 6 Notebook10min
Module 6 Exercise10min
Coronavirus data analysis10min
1 exercício prático
Modules 1 to 5
5 horas para concluir
Week 3
In week 3, its time to start analyzing data, now that you can write some code and import your data. The two most important steps to understand the message hidden in data, are to summarize and visualize it. Descriptive statistics turn rows and columns of data into something that we as humans can understand. By summarizing values and replacing them with single values, we start to get an idea of what our analyses might show. Visualizing the data is an even better way of getting to grips with data. Box-and-whisker plots, scatter plots, bar charts, and the like are wonderful ways to augment your understanding of the data. The Wolfram Language makes summary statistics easy but it really shines when creating plots. There are almost no limits to customizing plots. No matter what your project requirements, you will learn to create plots that work for you. Starting this week is an optional Honors lessons that introduce machine learning using the Wolfram Language.
5 horas para concluir
27 vídeos (Total 153 mín.), 10 leituras, 2 testes
27 videos
Descriptive statistics49s
Data import for descriptive statistics5min
Creating lists for descriptive statistics8min
Point estimates10min
Measures of dispersion6min
Data Visualization39s
Data import for visualization2min
Scatter plots10min
Box plots3min
Histograms5min
Bar and pie charts6min
Distributions1min
Probability8min
PDF and CDF3min
Discrete distributions7min
Continuous distributions6min
Sampling distributions6min
Simulated data6min
01: Introduction to neural networks46s
02: Introduction to machine learning6min
03: The fundamentals25s
04: Basic framework of a neural network10min
05: Layers in a neural network11min
06: Reviewing a neural network4min
07: From inputs to predictions6min
08: Finding a solution10min
10 leituras
Welcome to Module 710min
Module 7 Notebook10min
Module 7 Exercise10min
Welcome to Module 810min
Module 8 Notebook10min
Module 8 Exercise10min
Welcome to Module 910min
Module 9 Notebook10min
Module 9 Exercise10min
Neural networks in the Wolfram language10min
2 exercícios práticos
Modules 6 to 9
Honors: Deep learning basics1h
5 horas para concluir
Week 4
This final week covers all the common statistical tests - going from Student's t-test to analysis of variance to chi-squared tests. We conclude the course with a run-through of the demonstration research project that you saw at the beginning of week two. This brings together all the skills that you have acquired during the course and prepares you for the final exam. You will also have the opportunity to create your own computational essay, if you are not content with just working through the demonstration project. For those following the optional Honors lessons there is an introduction to deep learning using the Wolfram Language.
5 horas para concluir
27 vídeos (Total 121 mín.), 13 leituras, 3 testes
27 videos
Linear regression36s
Importing data4min
Descriptive statistics and visualization3min
Linear model5min
Comparing means17s
Data import3min
Comparing two means8min
Comparing more than two means7min
Comparing categorical variables21s
Contingency tables7min
Chi-squared test3min
Creating a Computational Essay47s
Data import7min
Main research question6min
Secondary research questions7min
Congratulations on reaching the end20s
09: Introduction to Wolfram Language machine learning25s
10: Automated Machine Learning10min
11: Running an automated algorithm4min
12: Testing the automated algorithm3min
13: Setting the method to neural network3min
14: Normalizing the data7min
15: Manually created neural networks8min
16: Regression - part 14min
17: Regression - part 22min
18: Regression - part 37min
13 leituras
Welcome to Module 105min
Module 10 Notebook5min
Module 10 Exercise5min
Welcome to Module 115min
Module 11 Notebook5min
Module 11 Exercise5min
Welcome to Module 125min
Module 12 Notebook5min
Module 12 Exercise5min
Welcome to Module 1310min
Module 13 Notebook10min
Final Exam Instructions10min
Continuing your journey with deep neural networks10min
3 exercícios práticos
Modules 10 to 13
Final Exam
Honors: Deep learning functions1h
Sobre Universidade da Cidade do Cabo
The University of Cape Town is the oldest university in South Africa and is one of the leading research universities on the African continent. UCT has over 25 000 students, of whom 30% are postgraduate students. We offer degrees in six faculties: Commerce, Engineering & the Built Environment, Health Sciences, Humanities, Law, and Science. We pride ourself on our diverse student body, which reflects the many cultures and backgrounds of the region. We welcome international students and are currently home to thousands of international students from over 100 countries. UCT has a tradition of academic excellence that is respected world-wide and is privileged to have more than 30 A-rated researchers on our staff, all of whom are recognised as world leaders in their field. Our aim is to ensure that our research contributes to the public good through sharing knowledge for the benefit of society. Past students include five Nobel Laureates – Max Theiler, Alan Cormack, Sir Aaron Klug, Ralph Bunche and, most recently, J M Coetzee.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao adquirir o Certificado?
Quando você adquire o Certificado, ganha acesso a todo o material do curso, incluindo avaliações com nota atribuída. Após concluir o curso, seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
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