Acerca de este Curso

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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 15 horas para completar
Inglés (English)

Habilidades que obtendrás

Learn to use the Wolfram Language to summarize data and create plotsLearn to use the Wolfram Language to do common statistical tests
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 15 horas para completar
Inglés (English)

Instructor

ofrecido por

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Universidad de Ciudad del Cabo

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

2 horas para completar

Week 1

2 horas para completar
14 videos (Total 54 minutos), 8 lecturas
14 videos
The Klopper Research Group1m
Assumptions1m
Learning a computer language1m
Why the Wolfram language?7m
Getting Mathematica5m
The new Wolfram Cloud1m
The Wolfram Cloud1m
The Wolfram Programming Lab8m
Free-form input and Wolfram Alpha in the Cloud3m
Mathematica27s
Free-form input and Wolfram Alpha in the desktop7m
Help and documentation3m
Assignment notebooks4m
8 lecturas
How this Course Works10m
Welcome to Module 110m
Meet the Course Instructor10m
Module 1 Notebook10m
Welcome to Wolfram Cloud10m
Welcome to Module 310m
Module 3 Notebook10m
Module 3 Exercise10m
Semana
2

Semana 2

3 horas para completar

Week 2

3 horas para completar
20 videos (Total 100 minutos), 8 lecturas, 1 cuestionario
20 videos
Simulated data demonstration - part 11m
Simulated data demonstration - part 27m
Simple arithmetic30s
Addition and subtraction5m
Multiplication and division9m
Powers5m
Arithmetical order2m
Calculating a mean5m
Working with data40s
Lists part 17m
Lists part 23m
Tables7m
Index10m
Datasets9m
Selecting6m
Dataset functions3m
Creating lists from datasets2m
Spreadsheets6m
Spreadsheets in the cloud4m
8 lecturas
Welcome to Module 410m
Module 4 Notebook10m
Welcome to Module 510m
Module 5 Exercise10m
Welcome to Module 610m
Module 6 Notebook10m
Module 6 Exercise10m
Coronavirus data analysis10m
1 ejercicio de práctica
Modules 1 to 5
Semana
3

Semana 3

5 horas para completar

Week 3

5 horas para completar
27 videos (Total 153 minutos), 10 lecturas, 2 cuestionarios
27 videos
Descriptive statistics49s
Data import for descriptive statistics5m
Creating lists for descriptive statistics8m
Point estimates10m
Measures of dispersion6m
Data Visualization39s
Data import for visualization2m
Scatter plots10m
Box plots3m
Histograms5m
Bar and pie charts6m
Distributions1m
Probability8m
PDF and CDF3m
Discrete distributions7m
Continuous distributions6m
Sampling distributions6m
Simulated data6m
01: Introduction to neural networks46s
02: Introduction to machine learning6m
03: The fundamentals25s
04: Basic framework of a neural network10m
05: Layers in a neural network11m
06: Reviewing a neural network4m
07: From inputs to predictions6m
08: Finding a solution10m
10 lecturas
Welcome to Module 710m
Module 7 Notebook10m
Module 7 Exercise10m
Welcome to Module 810m
Module 8 Notebook10m
Module 8 Exercise10m
Welcome to Module 910m
Module 9 Notebook10m
Module 9 Exercise10m
Neural networks in the Wolfram language10m
2 ejercicios de práctica
Modules 6 to 9
Honors: Deep learning basics1h
Semana
4

Semana 4

5 horas para completar

Week 4

5 horas para completar
27 videos (Total 121 minutos), 13 lecturas, 3 cuestionarios
27 videos
Linear regression36s
Importing data4m
Descriptive statistics and visualization3m
Linear model5m
Comparing means17s
Data import3m
Comparing two means8m
Comparing more than two means7m
Comparing categorical variables21s
Contingency tables7m
Chi-squared test3m
Creating a Computational Essay47s
Data import7m
Main research question6m
Secondary research questions7m
Congratulations on reaching the end20s
09: Introduction to Wolfram Language machine learning25s
10: Automated Machine Learning10m
11: Running an automated algorithm4m
12: Testing the automated algorithm3m
13: Setting the method to neural network3m
14: Normalizing the data7m
15: Manually created neural networks8m
16: Regression - part 14m
17: Regression - part 22m
18: Regression - part 37m
13 lecturas
Welcome to Module 105m
Module 10 Notebook5m
Module 10 Exercise5m
Welcome to Module 115m
Module 11 Notebook5m
Module 11 Exercise5m
Welcome to Module 125m
Module 12 Notebook5m
Module 12 Exercise5m
Welcome to Module 1310m
Module 13 Notebook10m
Final Exam Instructions10m
Continuing your journey with deep neural networks10m
3 ejercicios de práctica
Modules 10 to 13
Final Exam
Honors: Deep learning functions1h

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