Careers360 Logo
Interested in this College?
Get updates on Eligibility, Admission, Placements Fees Structure
Compare

Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf StudyVideo and Text Based

Courses and Certificate Fees

Fees InformationsCertificate AvailabilityCertificate Providing Authority
INR 2436yesCoursera

The fees for the course Doing Clinical Research: Biostatistics with the Wolfram Language is -

HeadAmount in INR
Certificate FeesRs. 2,436

 


The Syllabus

Videos
  • Welcome
  • The Klopper Research Group
  • Assumptions
  • Learning a computer language
  • Why the Wolfram language?
  • Getting Mathematica
  • The new Wolfram Cloud
  • The Wolfram Cloud
  • The Wolfram Programming Lab
  • Free-form input and Wolfram Alpha in the Cloud
  • Mathematica
  • Free-form input and Wolfram Alpha in the desktop
  • Help and documentation
  • Assignment notebooks
Readings
  • How this Course Works
  • Welcome to Module 1
  • Meet the Course Instructor
  • Module 1 Notebook
  • Welcome to Wolfram Cloud
  • Welcome to Module 3
  • Module 3 Notebook
  • Module 3 Exercise
Discussion prompts
  • Introduce Yourself
  • Optional Assignment - share your first Wolfram Notebook

Videos
  • Create Your Own Computational Essay
  • Simulated data demonstration - part 1
  • Simulated data demonstration - part 2
  • Simple arithmetic
  • Addition and subtraction
  • Multiplication and division
  • Powers
  • Arithmetical order
  • Calculating a mean
  • Working with data
  • Lists part 1
  • Lists part 2
  • Tables
  • Index
  • Datasets
  • Selecting
  • Dataset functions
  • Creating lists from datasets
  • Spreadsheets
  • Spreadsheets in the cloud
Readings
  • Welcome to Module 4
  • Module 4 Notebook
  • Welcome to Module 5
  • Module 5 Exercise
  • Welcome to Module 6
  • Module 6 Notebook
  • Module 6 Exercise
  • Coronavirus data analysis
Assignment
  • Modules 1 to 5

Videos
  • Summary Statistics
  • Descriptive statistics
  • Data import for descriptive statistics
  • Creating lists for descriptive statistics
  • Point estimates
  • Measures of dispersion
  • Data Visualization
  • Data import for visualization
  • Scatter plots
  • Box plots
  • Histograms
  • Bar and pie charts
  • Distributions
  • Probability
  • PDF and CDF
  • Discrete distributions
  • Continuous distributions
  • Sampling distributions
  • Simulated data
  • 01: Introduction to neural networks
  • 02: Introduction to machine learning
  • 03: The fundamentals
  • 04: Basic framework of a neural network
  • 05: Layers in a neural network
  • 06: Reviewing a neural network
  • 07: From inputs to predictions
  • 08: Finding a solution
Readings
  • Welcome to Module 7
  • Module 7 Notebook
  • Module 7 Exercise
  • Welcome to Module 8
  • Module 8 Notebook
  • Module 8 Exercise
  • Welcome to Module 9
  • Module 9 Notebook
  • Module 9 Exercise
  • Neural networks in the Wolfram language
Assignment
  • Modules 6 to 9
  • Honors: Deep learning basics

Videos
  • Inferential Statistics
  • Linear regression
  • Importing data
  • Descriptive statistics and visualization
  • Linear model
  • Comparing means
  • Data import
  • Comparing two means
  • Comparing more than two means
  • Comparing categorical variables
  • Contingency tables
  • Chi-squared test
  • Creating a Computational Essay
  • Data import
  • Main research question
  • Secondary research questions
  • Congratulations on reaching the end
  • 09: Introduction to Wolfram Language machine learning
  • 10: Automated Machine Learning
  • 11: Running an automated algorithm
  • 12: Testing the automated algorithm
  • 13: Setting the method to neural network
  • 14: Normalizing the data
  • 15: Manually created neural networks
  • 16: Regression - part 1
  • 17: Regression - part 2
  • 18: Regression - part 3
Readings
  • Welcome to Module 10
  • Module 10 Notebook
  • Module 10 Exercise
  • Welcome to Module 11
  • Module 11 Notebook
  • Module 11 Exercise
  • Welcome to Module 12
  • Module 12 Notebook
  • Module 12 Exercise
  • Welcome to Module 13
  • Module 13 Notebook
  • Final Exam Instructions
  • Continuing your journey with deep neural networks
Assignment
  • Modules 10 to 13
  • Final Exam
  • Honors: Deep learning functions

Instructors

Back to top