What are the most common data analysis communities for IE professionals?

Linked in Yehia arafa Asmaa Metwally Atef abdelfattah Samar soliman Symbios Consulting All of them and more are having communities on LinkedIn and whatsapp groups. They deliver courses, sessions, and conferences that would help a lot everyone to get used to that community 👌

It is wrong question. You can used to search answers online or in foums but sometime answer for hard and urgent topic come to you from enother place. This one may worth ten others... What you need is to be open and use all oportunities to get something new, to feed your curiosity. Hence my unswer would be us all of them 1Online forums 2Online courses 3Online groups 4Online blogs 5Online magazines 6Online events 7Here’s what else to consider

The Python community is very active and vibrant in Brazil. The Python Brazil Association (APyB) is a non-profit organization that promotes the Python language in the country. They organize the Python Brazil conference, which is an annual event that brings together developers, enthusiasts, and companies that use Python. The conference is a great opportunity to learn more about the language, meet other developers, and participate in interesting discussions.

I have found very helpful to use online forums during my learning process. However, being so accessible and popular also has its negative side. Sometimes there are too many threads about one topic and many of them are misleading.

It will always depend on the issue you have in your hands times all of them are useful for on-the-fly searches and can get you fast answers to common topics it will always depend on the difficulty of a problem. Online Forums are my go-to in the majority of cases.

Existem diversas comunidades e grupos que podem ser úteis para compartilhar conhecimentos, obter apoio e se conectar com outros profissionais da área. Alguns dos mais comuns são: 1. Kaggle 2. Data Science Society 3. Data Science Central 4. LinkedIn 5. Meetup

Here are some commonly used platforms for data analysis and information extraction: 1. Kaggle. 2. Stack Overflow. 3. GitHub. 4. Reddit (e.g., r/datascience, r/MachineLearning). 5. LinkedIn Groups. 6. Data Science Central. 7. Towards Data Science on Medium. 8. DataCamp Community.

Here are some useful ones, depending on the detail you 'd need, the source might change: Informs Connect Research Gate Reddit Quora Linkedin groups

Je trouve cette communauté formidable. Malheureusement, elle n'est pas bien connue du côté de l'Afrique de l'ouest de nos jours. Cela s'explique par le rythme même de notre évolution technologique et de la limitation de nos moyens d'accès à Internet.

Na atualidade temos diversos sites que oferecem cursos online gratuitos e pagos. Posso recomendar alguns: - Conquer - FM2S - EBAC online - Udemy - Codecademy

Cursos online são uma excelente forma de se atualizar ou recomeçar qualificações profissionais e conhecer mais sobre assuntos relacionados a sua área de atuação. Particularmente, sempre fui a favor da Udemy, como plataforma inicial e indico a quem procura novas qualificações.

- MIT OpenCourseWare offers free course materials from MIT's actual industrial engineering and management courses. - edX has courses from renowned universities in topics like Lean Six Sigma, systems engineering, and data analysis, which are highly relevant for IE professionals. It's my favorite.

Siempre es bueno buscar la actualización y la superación personal día a día, en lo personal me gusta contar con este tipo de oportunidades..

Acredito que com a dinâmica que o mundo está atualmente, cursos que são ofertados de modo online são extremamente fundamentais para todos que desejam se qualificar e necessitam ter opções mais dinâmicas. Posso recomendar diversas plataformas que oferecem cursos tanto gratuitos quanto pagos, com qualificações para diversos seguimentos. - Udemy - Data Science Academy - Engeteles - Modular - Bureau Veritas EAD...

A praticidade de estudar em horários variados e compatíveis com minha agenda me atraem muito nos cursos online em comparação aos presenciais . Exemplos de cursos online que recomendo são os da Conquer, Coursera e da USP.

Coursera: Coursera offers a wide range of courses in industrial engineering, data analysis, and related topics. Institutions like Georgia Tech, University of Washington, and others provide courses that cover various aspects of industrial engineering and data analysis. edX: Similar to Coursera, edX partners with universities and institutions to provide online courses. MIT, UC Berkeley, and other institutions offer courses on topics relevant to industrial engineering and data analysis. DataCamp: DataCamp focuses specifically on data science and analytics. It provides hands-on courses in programming languages like Python and R

De plus en plus, les acteurs évoluant dans le domaine de l'analyse des données trouvent pertinent d'adhérer à ce genre de communauté. Cette adhésion se fait en fonction de leurs besoins et de leurs disponibilités car tout cela est pris en compte par la communauté en question. Elle permet aujourd'hui aux intéressés d'apprendre ou d'approfondir leurs connaissances tout en continuant à travailler.

Sites que oferecem excelentes cursos e alguns gratuitos Voitto, Coursera, Labone, FM2S, EDTI, Udemy, Buzzero, Fundação Bradesco.

Fazer ou participar de qualquer curso que envolve ferramentas de análises de dados são excelentes iniciativas para desenvolver habilidades de análises críticas das situações do dia a dia na indústria.

LinkedIn Groups: Industrial Engineering Network: A group for industrial engineers to connect and share information. Data Science & Machine Learning: Join groups related to data science to connect with professionals in the field. Reddit: r/industrialengineering: The industrial engineering subreddit on Reddit where professionals and students discuss various aspects of the field. r/datascience: A subreddit focused on data science discussions. INFORMS Connect: INFORMS hosts various communities and forums related to operations research, management science, and analytics.

En la actualidad es una herramienta bastante potente, acortando la distancia del conocimiento. En lo personal me ha permitido seguir avanzando en el conocimiento de nuevas herramientas para implementar en el desarrollo como profesional. Esto permite crear buenos y nuevos lazos con personas de distintos lugares, creando una nueva comunidad.

I am part of several online groups and I found it great to connect with people. It is important to share ideas, learm from other professionals and sometimes even make friends. I recommend everyone to join online groups and keep them active because it is helpful for us and also for people that have different interests.

Le système de réseautage se développe de mieux en mieux maintenant. Les principaux canaux utilisés vers ici sont LinkedIn et Skype. Il permet aux intéressés d'apprendre les uns des autres dans un esprit de partage.

Assim como é importante ler livros, também é importante participar de grupos online para se atualizar do que está acontecendo no mundo na área de interesse.

LinkedIn: Join groups like Industrial Engineering Network, Data Analysis and Data Science, and Lean Six Sigma for professional discussions and networking. Facebook: Engage in groups such as Industrial Engineering, Data Analysis and Data Science, and Lean Six Sigma to connect with IE professionals interested in data analysis. Meetup: Explore local groups and events on Meetup, like Industrial Engineering Meetup and Data Analysis and Data Science Meetup, to network with professionals in person or virtually.

Hier sind einige empfehlenswerte Online-Communities: LinkedIn Gruppen: Plattformen wie "Industrial Engineering Network" oder "Data Science & Machine Learning" bieten hervorragende Möglichkeiten zum Netzwerken, Austauschen von Ideen und für Karrierechancen. Facebook Gruppen: Hier gibt es zahlreiche Gruppen wie „Data Science World“ oder „Industrial Engineering & Management“, die eine Plattform für Diskussionen, Ratschläge und das Teilen von Ressourcen bieten. Reddit: Subreddits wie r/dataisbeautiful oder r/engineering und r/industrialengineering ResearchGate: Hier können Sie sich mit anderen Wissenschaftlern verbinden, Forschungspapiere austauschen und Diskussionen über aktuelle Themen führen.

the challenge with online groups shows its ugly face when the executive part of our contribution kicks in. its difficult to be aware and attendant to such threads while simultaneously running teams and or projects. this is something my team and associates have pretty much stopped. the interpersonal communication is lost. we have a saying, if they advice available is free, it has little to no value. advice is always worth exactly the cost.

Acá la opciones crecen exponencialmente, desde plataformas virtuales extremadamente profesionales como LinkedIn o inclusive algo más coloquial como Facebook ofrecen grupos de Data Science o Lean Manfucacturing u otros focos de IE. Como conclusión me gustaría proponer que en nuestras redes de contactos podamos formar grupos de este tipo más personalizados, ya que se concentran las teorías de manera aplicada a la industria. Esto efectivamente se puede lograr en LinkedIn, WhatsApp u otra RRSS.

Real Python: Real Python offers a wide range of tutorials and articles catering to various skill levels. Topics include Python fundamentals, web development, data science, and more. Python.org Blog: The official blog for the Python programming language. It provides updates on the latest releases, events, and important announcements related to the Python community.

Os blogs com foco em um determinado assunto ou ferramenta, são excelentes meios para obter conhecimento e estar informado do que está acontecendo na área.

The IE Zone: Dive into articles, case studies, and resources covering a spectrum of IE topics, including data analysis, optimization, simulation, and quality. DataCamp: Sharpen your data analysis skills with tutorials, courses, and projects offered by DataCamp, focusing on data science, machine learning, and tools like Excel, Python, and R. Lean Blog: Explore Lean Blog for in-depth insights into lean, six sigma, and continuous improvement practices, including podcasts, webinars, and books tailored for IE professionals engaged in data analysis.

Os blogs são interessantes porque normalmente discorrem sobre os assuntos com uma abordagem mais prática e direta, ou seja, técnicos, mas sem rodeios.

Buenos blogs asociados a la predicción de fallas son: -Infraspeaks -Predictiva21 Buenos blogs de data (Science y Analytics) son: -Datdata -Towards -Vidhya -Dataconomy Buenos blogs de Lean son: -Shinka -Escuela Lean Por lo demas, respecto de las metodologías Lean o su génesis Kaizen recomiendo seguir al Sensei Kouichii Kimura. Para aprender herramientas un poco más disruptivas en términos culturales asociados a IE.

Real Python Magazine: Real Python offers a magazine subscription that provides in-depth articles, tutorials, and case studies on various Python-related topics. It's available in both digital and print formats. PSF News: The official blog of the Python Software Foundation (PSF) occasionally features news, updates, and announcements related to the Python programming language. The Python Papers: While not regularly updated, The Python Papers Anthology is an online publication that compiles articles and research papers related to Python. It includes content on a variety of Python-related topics.

Exist serveral online news Worldwide nevertheless, is important consider the news that contribuit with true information but as well neutral information that can contribuit to take a oriented decision to a positive result, not considering one way only. This can be different according your country or región, exist some that supply information according specific markets.

ISE Magazine (Institute of Industrial and Systems Engineers): Explore articles on data analysis, operations research, ergonomics, and sustainability in ISE Magazine, a publication by IISE. Analytics Magazine: Stay updated on the latest trends, technologies, and applications of analytics through Analytics Magazine, providing valuable insights into the world of data analysis. Quality Digest: Dive into articles on quality, performance, and improvement in Quality Digest, covering topics like statistical process control, design of experiments, and root cause analysis.

Uma revista online que li e aprofundei análise de dados foi a revista Programar, a revista publicou um artigo completo sobre Python que aborda a história e ascendência sobre o tema.

Las revistas en línea son recursos que aportan conocimiento. Solo debemos tener en claro qué buscar, para saber qué encontrar.

Respecto de las revistas y el magazine de ingeniería industrial en general vemos que constantemente crece y se más popular dentro de la comunidad de ingenieros, respecto de mi experiencia los que más han significado un apoyo, tanto en metodologías aplicables a la industria como saber general son: 1. Predictiva21 2. Planet Engineering 3. Revist Byte 4. Data Magazine

PyCon Online: PyCon is one of the largest annual conferences for the Python community. While physical conferences are held worldwide, PyCon Online offers virtual events, talks, tutorials, and discussions. EuroPython: EuroPython is another major Python conference, and they often organize virtual events with presentations, workshops, and discussions.

In order to be a great professional our knowledge needs to evolve with the development of technology. Online events are very helpful to keep us up to date with new technologies as they are very flexible in terms of time and location.

Hier sind einige Plattformen und Veranstaltungstypen, die besonders hervorzuheben sind: Online-Konferenzen: Große Konferenzen wie die "International Conference on Industrial Engineering and Operations Management" oder "Data Science Conference" und "PyCon Online" haben oft Online-Optionen, die es ermöglichen, an Keynotes und Panels von weltweit führenden Experten teilzunehmen. Online-Kurse mit Live-Sessions: Einige Online-Kurse auf Plattformen wie Coursera oder edX bieten Live-Sessions an, in denen Teilnehmer direkt mit Dozenten und Experten interagieren können.

Comenzare restringiendo este apartado comentando que, de todos los puntos de contribución, este es el menos estandarizado y es que, por su dinámica y variabilidad a través del tiempo, será que nos encontraremos con una serie de seminarios y otros eventos interesantes asociados a temas de IE. Para acotar con la generalidad que merece este apartado recomiendo totalmente cualquier evento asociado a instituciones de alto nivel científico como: -PUCV -PUC -MIT No obstante, gran mención a las siguientes organizaciones: -TRACTIAN -DATDATA

In addition to above, some of the most common communities for data analysts in industrial engineering include: 1. Institute of Industrial and Systems Engineers (IISE): The IISE offers a platform for industrial engineering professionals to discuss data analysis techniques, best practices, and the application of data analytics in industrial settings. 2. Kaggle:Kaggle is a platform for data science and machine learning enthusiasts. 3. Reddit:Subreddits such as r/industrialengineering and r/dataanalysis are popular among professionals looking to discuss industrial engineering topics and data analysis techniques. 4. Local Meetup Groups:Many cities have local meetup groups focused on data analysis, industrial engineering, or related fields.

No hay una sola respuesta correcta, la elección de la comunidad más adecuada para ti dependerá de tus preferencias, necesidades y objetivos. Lo importante es que te mantengas actualizado, conectado con las tendencias y cambios donde es fundamental estar motivado con el mundo del análisis de datos.

Online courses offer unparalleled flexibility, catering to individuals with busy schedules or limited access to traditional education. With diverse subjects and expert-led content, learners can align their studies with specific interests and career goals. Cost-effective and often supplemented with free resources, online courses provide interactive elements like quizzes and forums, enhancing the overall learning experience and promoting active engagement.

Cuando uno de los temas de fondo es puesto como prioridad en el foco de desarrollo profesional propio, resulta interesante contextualizar a lo menos en un pequeño porcentaje el uso de nuestras redes sociales coloquiales, a lo menos en un pequeño porcentaje, esto junto con el correcto uso de las herramientas planteadas en los 6 puntos anteriores, a mi juicio, marcarán la diferencia.