Statistics and Probabilistic Programming in Julia Training Course
This instructor-led, live training (online or onsite) is aimed at people that already have a background in data science and statistics.
Format of the Course
- Interactive lecture and discussion.
- Exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Statistics & Probabilistic Programming in Julia
Basic statistics
- Statistics
- Summary Statistics with the statistics package
- Distributions & StatsBase package
- Univariate & multivariate
- Moments
- Probability functions
- Sampling and RNG
- Histograms
- Maximum likelihood estimation
- Product, trucation, and censored distribution
- Robust statistics
- Correlation & covariance
DataFrames
(DataFrames package)
- Data I/O
- Creating Data Frames
- Data types, including categorical and missing data
- Sorting & joining
- Reshaping & pivoting data
Hypothesis testing
(HypothesisTests package)
- Principle outline of hypothesis testing
- Chi-Squared test
- z-test and t-test
- F-test
- Fisher exact test
- ANOVA
- Tests for normality
- Kolmogorov-Smirnov test
- Hotelling's T-test
Regression & survival analysis
(GLM & Survival packages)
- Principle outline of linear regression and exponential family
- Linear regression
- Generalized linear models
- Logistic regression
- Poisson regression
- Gamma regression
- Other GLM models
- Survival analysis
- Events
- Kaplan-Meier
- Nelson-Aalen
- Cox Proportional Hazard
Distances
(Distances package)
- What is a distance?
- Euclidean
- Cityblock
- Cosine
- Correlation
- Mahalanobis
- Hamming
- MAD
- RMS
- Mean squared deviation
Multivariate statistics
(MultivariateStats, Lasso, & Loess packages)
- Ridge regression
- Lasso regression
- Loess
- Linear discriminant analysis
- Principal Component Analysis (PCA)
- Linear PCA
- Kernel PCA
- Probabilistic PCA
- Independent CA
- Principal Component Regression (PCR)
- Factor Analysis
- Canonical Correlation Analysis
- Multidimensional scaling
Clustering
(Clustering package)
- K-means
- K-medoids
- DBSCAN
- Hierarchical clustering
- Markov Cluster Algorithm
- Fuzzy C-means clustering
Bayesian Statistics & Probabilistic Programming
(Turing package)
- Markov Chain Model Carlo
- Hamiltonian Montel Carlo
- Gaussian Mixture Models
- Bayesian Linear Regression
- Bayesian Exponential Family Regression
- Bayesian Neural Networks
- Hidden Markov Models
- Particle Filtering
- Variational Inference
Requirements
This course is intended for people that already have a background in data science and statistics.
Open Training Courses require 5+ participants.
Statistics and Probabilistic Programming in Julia Training Course - Booking
Statistics and Probabilistic Programming in Julia Training Course - Enquiry
Statistics and Probabilistic Programming in Julia - Consultancy Enquiry
Consultancy Enquiry
Testimonials (5)
The variation with exercise and showing.
Ida Sjoberg - Swedish National Debt Office
Course - Econometrics: Eviews and Risk Simulator
the trainer had patience, and was eager to make sure we all understood the topics, the classes were fun to attend
Mamonyane Taoana - Road Safety Department
Course - Statistical Analysis using SPSS
Day 1 and Day 2 were really straight forward for me and really enjoyed that experience.
Mareca Sithole - Africa Health Research Institute
Course - R Fundamentals
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
Upcoming Courses
Related Courses
Algorithmic Trading with Python and R
14 HoursThis instructor-led, live training in Norway (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.
By the end of this training, participants will be able to:
- Employ algorithms to buy and sell securities at specialized increments rapidly.
- Reduce costs associated with trade using algorithmic trading.
- Automatically monitor stock prices and place trades.
Programming with Big Data in R
21 HoursBig Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.
Introductory R (Basic to Intermediate)
14 HoursThis instructor-led, live training in Norway (online or onsite) is aimed at beginner-level data analysts who wish to use R programming to manipulate data, perform basic data analysis, and create compelling visualizations for insights.
By the end of this training, participants will be able to:
- Understand the basics of R Programming.
- Apply fundamental data science processes.
- Create visual representations of data.
R Fundamentals
21 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
Cluster Analysis with R and SAS
14 HoursThis instructor-led, live training in Norway (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis.
By the end of this training, participants will be able to:
- Use cluster analysis for data mining
- Master R syntax for clustering solutions.
- Implement hierarchical and non-hierarchical clustering.
- Make data-driven decisions to help to improve business operations.
Data and Analytics - from the ground up
42 HoursData analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions:
What has happened?
- processing and analyzing data
- producing informative data visualizations
What will happen?
- forecasting future performance
- evaluating forecasts
What should happen?
- turning data into evidence-based business decisions
- optimizing processes
The course itself can be delivered either as a 6 day classroom course or remotely over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
Data Analysis with Python, R, Power Query, and Power BI
21 HoursThis instructor-led, live training in Norway (online or onsite) is aimed at beginner-level professionals who wish to clean and analyze data, make statistical projections, and create insightful visualizations using these tools.
By the end of this training, participants will be able to:
- Understand the basics of Python, R, Power Query, and Power BI for data analysis.
- Clean and organize datasets using Python and Power Query.
- Perform statistical analysis and projections with R.
- Create professional dashboards and reports with Power BI.
- Integrate and analyze data from multiple sources effectively.
Data Analytics With R
21 HoursR is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students. It covers language fundamentals, libraries and advanced concepts. Advanced data analytics and graphing with real world data.
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
Data Mining with R
14 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
Econometrics: Eviews and Risk Simulator
21 HoursThis instructor-led, live training in Norway (online or onsite) is aimed at anyone who wishes to learn and master the fundamentals of econometric analysis and modeling.
By the end of this training, participants will be able to:
- Learn and understand the fundamentals of econometrics.
- Utilize Eviews and risk simulators.
HR Analytics for Public Organisations
14 HoursThis instructor-led, live training (online or onsite) is aimed at HR professionals who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Statistical Analysis using SPSS
21 HoursThis instructor-led, live training in Norway (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to perform statistical analysis using SPSS to interpret data accurately, run complex statistical tests, and generate meaningful insights.
By the end of this training, participants will be able to:
- Navigate the SPSS interface and manage datasets efficiently.
- Perform descriptive and inferential statistical analyses.
- Conduct t-tests, ANOVA, MANOVA, regression, and correlation analyses.
- Apply non-parametric tests, principal component analysis, and factor analysis for advanced data interpretation.
Talent Acquisition Analytics
14 HoursThis instructor-led, live training (online or onsite) is aimed at HR professionals and recruitment specialists who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Introduction to Data Visualization with Tidyverse and R
7 HoursThe Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.
In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.
By the end of this training, participants will be able to:
- Perform data analysis and create appealing visualizations
- Draw useful conclusions from various datasets of sample data
- Filter, sort and summarize data to answer exploratory questions
- Turn processed data into informative line plots, bar plots, histograms
- Import and filter data from diverse data sources, including Excel, CSV, and SPSS files
Audience
- Beginners to the R language
- Beginners to data analysis and data visualization
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice