Join our workshop on Meta-Analysis in R, which is a part of our workshops for Ukraine series! 

Here’s some more info: 

Title: Meta-Analysis in R

Date: Thursday, July 11th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

Speaker: Matthew B. Jané is a graduate student in quantitative psychology at the University of Connecticut. His interests involve data visualization and statistical methods for meta-analysis and psychometric measurement. He is affiliated with the Systematic Health Action Research Program where he is advised by Dr. Blair T. Johnson. 

Description: In this workshop, we will learn how to conduct meta-analysis in R using real data sets. We will first discuss how effect sizes such as standardized mean differences, correlations, and odds ratios are calculated. Then we will discuss three types of meta-analytic models (i.e., common, fixed, and random effects models) and how we can fit each model in R. Finally, we will visualize how study characteristics can moderate effect sizes with the help of meta-regression.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

How can I register?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or  https://bit.ly/3PFxtNA and donate at least 20 euro. Feel free to donate more if you can, all proceeds go directly to support Ukraine.

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or https://bit.ly/3PFxtNA and donate at least 20 euro (or 17 GBP or 20 USD or 800 UAH). Feel free to donate more if you can, all proceeds go to support Ukraine!

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

Looking forward to seeing you during the workshop!

Join our workshop on Effective Visual Communication with R, which is a part of our workshops for Ukraine series! 

Here’s some more info: 

Title: Effective Visual Communication with R

Date: Thursday, June 20th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

Speaker: Claus Wilke is a data scientist and computational biologist at The University of Texas at Austin. He is known for his work on popular R packages for data visualization, such as cowplot, ggridges, and ggtext, as well as his contributions to the package ggplot2. He is also the author of the book Fundamentals of Data Visualization, published in 2019, which provides a concise introduction to effectively visualizing many different types of data sets.

Description: In the first half of this workshop, Wilke will provide a high-level perspective on how to make good visualizations and how to use them effectively to communicate and reason about data. The second half will be more hands-on and will address how to use R to make interactive plots, deal with overplotting, and make compound figures.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

How can I register?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or  https://bit.ly/3PFxtNA and donate at least 20 euro. Feel free to donate more if you can, all proceeds go directly to support Ukraine.

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or https://bit.ly/3PFxtNA and donate at least 20 euro (or 17 GBP or 20 USD or 800 UAH). Feel free to donate more if you can, all proceeds go to support Ukraine!

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

Looking forward to seeing you during the workshop!

ChatGPT was only the beginning. Generative AI is now revolutionizing every industry. 

As the race to adopting AI tools intensifies, the decisions we make today about AI will likely shape our success for decades to come.

To learn how the world’s data and AI leaders are adapting to this new era, join DataCamp on June 26–27 for RADAR: AI—a two-day digital event exploring how businesses and individuals can unlock their full potential with AI.

Register Now

From scaling AI within your organization and driving innovation to navigating the evolving job market, uncover practical steps to implement in your career or organization to maximize the power of generative AI.

A star-studded agenda:

Including voices from GitHub, Dropbox, PwC, Hugging Face, Accenture, and many more, unpack how AI is evolving and how you can take advantage.

A peak at what to you can expect:

June 27, 2024 (all times EDT):

9:00–9:45
Welcome to RADAR!
Jonathan Cornelissen, Co-Founder & CEO, DataCamp

9:50–10:35

Generative AI in Practice: 100+ Amazing Ways Generative AI is Changing Business and Society 

Bernard Marr, World-renowned Futurist, AI Advisor, and Author of “Generative AI in Practice”, Bernard Marr & Co

10:50–11:35 

From Learning to Earning: Navigating the AI Job Landscape

Sadie St Lawrence, Founder & CEO at Women in Data, and Megan Finck,

Global Head of Talent Acquisition—Engineering, IT and Data Analytics, Boeing

11:40–12:25

Generative AI: Trends, Impact, and Practical Applications for 2024

Principal, Insight Partners, and Sandhya Venkatachalam, Partner, Axiom Partners

12:40–1:25 

The High Cost of AI Hype

Eric Siegel, Founder of Machine Learning Week, Prediction Impact

1:30–2:15
Building Tomorrow’s Workforce, Today: Scaling Internal AI Academies
Mike Baylor, CDAO, Lockheed Martin, Carolann Diskin, Senior Technical Program Manager, Dropbox, Matthew Graviss, and CDAIO, U.S. Department of State

2:20–3:05

Scaling Data Quality in the Age of Generative AI

Barr Moses, CEO, Monte Carlo Data, Prukalpa Sankar, Co-founder, Atlan, and George Fraser CEO, Fivetran

June 27, 2024

9:00–9:45
Building Trust in AI: Scaling Responsible AI Within Your Organization

Haniyeh Mahmoudian, Chief AI Ethicist at Datarobot, Eske Montoya Martinez van Egerschot, Chief AI Governance and Ethics at DigiDiplomacy, Associate Partner at Meines Holla & Partners, and Alexandra Ebert, Chief Trust Officer at MOSTLY AI

9:50–10:35 

Leading with AI: Leadership Insights on Driving Successful AI Transformation

Chandra Donelson, Chief Data and Analytics Officer at United States Air Force, Semih Kumluk, Head of AI and Digital at PwC, and Giorleny Altamirano Rayo

10:50–11:35 

The Future of Programming: Accelerating Coding Workflows with LLMs

Michele Catasta, VP of AI at Replit, Jordan Tigani, CEO at Mother Duck, and Ryan J. Salva, VP of Product at GitHub

11:40–12:25 

Hugging Face and the Future of the Open Source AI Ecosystem

Julien Simon, Chief Evangelist at Hugging Face

12:40–13:25 

Building an AI Strategy: Key Steps for Aligning AI with Business Goals

Vin Vashishta, AI Advisor and Founder of V Squared, Cindi Howson, Chief Data Strategy Officer at ThoughtSpot, and Sonali Bhavsar, Managing Director at Accenture

13:30–14:15 

Charting the Path: What the Future Holds for Generative AI
Edo Liberty, CEO at Pinecone, Tomasz Tunguz, General Partner at Theory Ventures, and Nick Elprin, CEO at Domino Data Lab

14:20–15:05

Closing Session & AMA

DataCamp’s Co-founders, Jonathan Cornelissen, CEO, and, Martijn Theuwissen, COO

Once again, RADAR AI is free for everyone

Radar: AI is more than just another AI conference, but a place to connect with like-minded individuals and organizations. Whether you’re a data scientist, business leader, or just AI-curious, Radar: AI Edition offers something for everyone.

Don’t let the data and AI revolution pass you by.

Register Now

Transform your career with vital data and AI skills.

Designed for all levels—whether you’ve never written a line of code or you’re an advanced data science practitioner—secure half-price learning across the world’s most in-demand data and AI skills.

Save Now

What do I get with a DataCamp Premium Subscription? 

480+ interactive courses for all levels

From generative AI basics to advanced programming and Business Intelligence tooling, unlock DataCamp’s entire interactive course library: including Python, ChatGPT, SQL, Power BI, and more

Tailored Career and Skill Tracks

Take the stress out of learning with bespoke learning paths. Start from scratch and develop job-ready skills built for in-demand career personas, such as Data Scientist/Analyst in Python, Data Analyst in SQL, Machine Learning Scientist, and more.

Forbes’ #1 Ranked Certification Program

Developed with industry leaders, enhance your CV with DataCamp’s Certification program. From data and AI Fundamentals to Technology Certifications in Tableau, Power BI, and Alteryx to career-ready Data Scientist, Analyst, or Engineer options—find a route that suits your ambitions.

And much more. Gain unlimited access to DataCamp’s entire platform for half price.

Limited time only. Only valid for annual subscriptions for maximum savings.

Discover more

DataCamp is launching DataLab, an AI-enabled data notebook to make it easier and faster than ever before to go from data to insight, regardless of technical ability.

The challenge DataLab Solves

DataCamp’s mission to democratize data skills has translated into its leading online data and AI learning platform. 

Alongside learning, intuitive data tooling is vital for modern professionals to feel empowered to make data-driven decisions. But more often than not, tools today are getting in the way rather than helping us. Depending on your skill set, you need different tools (Excel, a SQL editor, a Python notebook). 

As a result, insights are scattered across functions and collaboration becomes a drag. And, insights are often separated by technical skills or needing to go through specialist data teams to get answers.

The solution: Democratized insights

DataLab is an AI-powered chat interface specifically tailored for data analytics. The steps are simple: attach a data source, ask a question, and iterate your way to the insight you need, just like you would with a technically skilled colleague.

DataLab is an AI-powered data notebook to chat with your data

DataLab’s key features:

• Powered by code. The AI Assistant answers your questions by writing and running code and interpreting the outputs. With DataLab, you can seamlessly switch to a fully-featured notebook view with all of the generated code, that you can review, tweak, extend, and share.
  
  
• Easy data access, wherever it lives. From CSV files and Google Sheets data to Snowflake and BigQuery: DataLab seamlessly and securely connects to all your data sources. DataLab’s AI architecture knows where to look and achieves best-in-class results by leveraging organizational knowledge, your previous activity, and industry best practices.
  
  
• Built-in reporting. Forget about copy-pasting across tools or sharing outdated screenshots of your findings. As you’re getting answers to questions in DataLab, you’re accumulating a live-updating report that you can customize before sharing with others with a single click.
  
  

DataLab’s chat interface looks similar to ChatGPT, and that’s the point! OpenAI managed to package extremely sophisticated technology into an intuitive interface. 

Just because technology is complex, doesn’t mean the interface needs to be.

DataLab’s path so far

DataLab is the next iteration of DataCamp Workspace, an online data notebook with more than 50,000 monthly active users and support for SQL, Python, and R. 

With the breakthrough of GPT-3.5 and many other LLMs in early 2023, DataCamp saw the opportunity to make their users even more effective and Workspace accessible to a bigger user base, both for study and work.

DataCamp added powerful AI features to write, update, fix, and explain code. The built-in Workspace AI Assistant is smarter than ChatGPT: it takes more context into account (variables, table names, and column types), leading to higher-quality suggestions and a faster workflow. 

DataLab is Workspace’s notebook environment plus an intuitive AI-powered chat interface. This means you’re getting the power of AI and a fully-fledged coding environment without switching tools. Real-time collaboration, scheduling, version history, role-based access control, you name it: you’re tapping into years of work building a data notebook that is intuitive and delightful to use, whether you’re learning on DataCamp or working through your unique projects.

I have used Workspace in the past, what happens to my work?

All your workspaces (now workbooks) you created in the past will stay available and continue to function. You can continue using DataLab for free (three workbooks, 20 AI Assistant prompts, basic hardware); all you need is your DataCamp account. 

Users on an existing Workspace Premium subscription can access DataLab Premium, featuring unlimited workbooks, unlimited AI Assistant prompts, powerful hardware, and more.

Try it out for free

• Visit www.datacamp.com/datalab
  
  
• Pricing: DataLab is publicly available now and free to try (up to 3 projects, up to 20 AI Assistant prompts). For $99/user/year you can create unlimited projects, use the AI assistant without limitations, and access more powerful hardware. See www.datacamp.com/datalab/pricing for more details.
  
  
• Interested in leveraging DataLab to drive insight in business data? Book a demo

Join our workshop on Cluster Analysis in R which is a part of our workshops for Ukraine series! 

Here’s some more info: 

Title: Cluster Analysis in R

Date: Thursday, June 6th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone) 

Speaker: Sejal Davla is a neuroscientist and data scientist who works with industry and government clients on projects at the intersection of science, data, and policy. She received her PhD in neuroscience from McGill University in Canada, where her research identified new pathways in brain development and sleep. She is an advocate for open science and reproducibility and runs R programming workshops to promote best data practices. 

Description: Some datasets are unlabeled without obvious classifiers. Unsupervised machine learning methods, such as clustering, allow finding patterns and homogeneous subgroups in unlabeled data. This workshop will cover the basics of cluster analysis and how to perform clustering using k-means and hierarchical clustering methods. The goal of the workshop is to help identify datasets for clustering, learn to visualize and interpret models, validate clusters, and highlight practical issues.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

How can I register?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or  https://bit.ly/3PFxtNA and donate at least 20 euro. Feel free to donate more if you can, all proceeds go directly to support Ukraine.

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or https://bit.ly/3PFxtNA and donate at least 20 euro (or 17 GBP or 20 USD or 800 UAH). Feel free to donate more if you can, all proceeds go to support Ukraine!

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

Looking forward to seeing you during the workshop!

Introduction

Hello everyone!
I’m excited to announce the release of our latest collaborative effort (R package), designed to make complex consumer price and inflation calculations a breeze: emWeightedCPI .
Here I will Introduce you to what this package is about.

What is emWeightedCPI?

Our R package “emWeightedCPI” (hosted on github) stands for Expenditure based and Multivariate Weighted Consumer Price Index. This is the result of the combined effort of myself and two other talented individuals; Dr Paul A. Agbodza and George K. Agyen . It is a versatile tool that simplifies the calculation of standard Consumer Price Indices (CPI) and Inflation using Expenditure based and Multivariate Weights. The package automates a proposed multivariate weighted indexing scheme for price data. More information can be found [here].

Why Create emWeightedCPI Package?

Normally CPI is calculated from household expenditure data obtained from household expenditure surveys. However, these surveys are expensive making it difficult to conduct on a regular basis. This package introduces an alternative weighting approach that enables the computation of variable weights using price data only.

This approach is convenient since it does not require incurring additional cost for conducting household expenditure survey to generate CPI for the determination of inflation figures. Even so, one can still generate the Laspeyres’ CPI and inflation using this package.

The workings of The package

Using emWeightedCPI is as easy as taking a stroll! Begin by installing the package from github by using

install.packages(“devtools”) 

devtools::install_github(“JC-Ayimah/emWeightedCPI”)

Once installed, load the package into your R environment with library(emWeightedCPI) . Now you’re all set to dive into the world emWeightedCPI and make use of its functions

How does emWeightedCPI work?

The package contains four main functions:

1. mvw_cpi: This function calculates the multivariate weighted indices . It requires only one argument (data); a price dataset containing prices of various items for a base year and a current year. It then calculates four index values (CPI values) based on the data provided and returns them as a named vector
2. mvw_inflation: Using the index values calculated by mvw_cpi, the mvw_inflation function computes the inflation rate based on the selected index. The function takes two arguments index and data . the index argument takes one of four possible values (indexes); ‘fisher’, ‘paashe’,‘laspeyres’ and ‘drobish’. The data argument requires the price dataset from which the inflation is to be determined.
3. eb_cpi: This function calculates consumer price indexI from expenditure based expenses. The function takes in two inputs, a price data and an expenditure data. The index calculated from this function is the ‘Laspeyres index’
4. eb_inflation: Like the mvw_inflation function, the eb_inflation function also calculates inflation based on the index calculated from the eb_cpi function. The function takes the same arguments specified in the eb_cpi function.
   
   Usage Examples

Lets create a price data containing the prices of 4 different items for a base year and current year.

#create an arbitrary price data

mypriceData <- data.frame(x1=runif(50, 9.9, 13.7), x2=rnorm(50, 10.9, 2.1), x3=runif(50, 12.2, 15), x4=runif(50,19.4, 24), # base year prices y1=runif(50, 26, 30), y2=runif(50, 31, 38.9), y3=runif(50, 28.2, 33.1), y4=runif(50, 51.8, 60)# current year prices )

To calculate the multivariate weighted indices simply use;

library(emWeightedCPI)

indices <- mvw_cpi(data = mypriceData)

indices

To calculate the multivariate weighted inflation based on a specific index (let’s say ‘fishers’) we use;

inflation_value <- mvw_inflation(index = ‘fisher’, data = mypriceData) inflation_value

The expenditure based index eb_cpi and inflation eb_inflation can also be calculated easily by using the codes as shown below. We need to generate an expenditure data to use together with our previously created price data in order to calculate the expenditure based index and inflation.

#pick the average base year prices from mypriceData

n_vec <- apply(mypriceData[, 1:4], 2, mean)

n_vec

 

#combine the output above into a dataframe with two columns and same

#number of rows as number of price items to create expenditure data

myexpData <- cbind.data.frame(item = names(n_vec), price = (unname(n_vec)))

myexpData

 

#calculate expenditure based CPI

exp_index <- eb_cpi(price_data = mypriceData, expenditure_data = myexpData)

exp_index

 

#calculate expenditure based Inflation

exp_inflation <- eb_inflation(mypriceData, myexpData)

exp_inflation

Conclusion

Innovation often thrives when minds come together, and emWeightedCPI is a testament to the power of collaboration. We’re incredibly proud of what we’ve achieved with this package, and we hope it becomes a valuable asset in your analytical toolkit.

Why Use emWeightedCPI?

1. Ease of Use: The functions in emWeightedCPI are designed to be intuitive and straightforward to use.
2. Flexibility: Users can customize the calculations based on their specific requirements by adjusting the input parameters especially for the mvw_inflation function
3. Efficiency: With optimized algorithms, emWeightedCPI delivers fast and accurate results.

Get Started with emWeightedCPI Today!

If you’re looking to simplify your consumer price index and inflation rate calculations in R, give emWeightedCPI a try! You can install it directly from github using:

install.packages(“devtools”)devtools::install_github(“JC-Ayimah/emWeightedCPI”)

For more information and detailed documentation, check out the emWeightedCPI GitHub repository.

We hope you find emWeightedCPI as useful and exciting as we do! Feel free to reach out with any questions, feedback, or suggestions.

Happy calculating!