AWS Ground Station presenta el Acelerador de licencias

AWS presenta el Acelerador de licencias, una nueva característica de AWS Ground Station que proporciona a las empresas industriales, a las empresas emergentes espaciales y a las universidades acceso a los recursos para ayudarles a obtener de manera más eficiente las licencias de espectro necesarias para sus operaciones y misiones. El Acelerador de licencias es gratuito para los clientes de AWS Ground Station. AWS Ground Station es un servicio totalmente administrado que permite a los clientes controlar las comunicaciones, procesar los datos de los satélites y escalar sus operaciones. Con el Acelerador de licencias, los clientes de AWS Ground Station pueden lanzar y escalar operaciones espaciales más rápidamente aprovechando la información más reciente y centralizada sobre las regulaciones de licencias de satélites, como las licencias de estaciones espaciales, las licencias de teledetección y la coordinación de la Unión Internacional de Telecomunicaciones (UIT).

Amazon EMR Studio ya es compatible con los blocs de notas basados en Jupyter en varios lenguajes para las cargas de trabajo de Spark

EMR Studio es un entorno de desarrollo integrado (IDE) que facilita a los científicos e ingenieros de datos el desarrollo, la visualización y la corrección de aplicaciones de big data y análisis escritas en R, Python, Scala y PySpark. Hoy nos complace anunciar que, a partir de EMR 6.4.0, se puede utilizar Python, Scala, SparkSQL y R dentro del mismo bloc de notas Jupyter en EMR Studio, lo que proporciona flexibilidad para utilizar diferentes lenguajes de programación para las cargas de trabajo de Spark.

Amazon ECR agrega la capacidad de replicar repositorios individuales a otras regiones y cuentas

Hoy, Amazon Elastic Container Registry (ECR) ha lanzado la capacidad de replicar repositorios específicos a cuentas o regiones, y ver cuándo se han replicado las imágenes a través de la API de ECR. Esto le da un control pormenorizado para replicar las imágenes que desee dentro de los repositorios, en lugar de replicar todas las imágenes de un registro, y la capacidad de automatizar acciones a través de la nueva API DescribeImageReplicationStatus cada vez que se replican las imágenes.

SageMaker Studio habilita procesamiento de datos basado en Spark interactivo desde blocs de notas de Studio

Amazon SageMaker anuncia un nuevo conjunto de capacidades que habilitarán el procesamiento de datos basado en Spark interactivo desde blocs de notas de SageMaker Studio. Amazon SageMaker Studio es el primer entorno de desarrollo completamente integrado (IDE) para el machine learning (ML). SageMaker Studio proporciona una única interfaz visual basada en la web donde se pueden realizar todos los pasos de desarrollo de ML necesarios para preparar los datos, así como crear, formar e implementar los modelos. Con un único clic, los científicos de datos y desarrolladores pueden poner en marcha con rapidez blocs de notas de Studio para explorar conjuntos de datos y crear modelos de ML.

AWS Amplify CLI y la interfaz de usuario de administración ya están disponibles de manera general en EE. UU. Oeste (Norte de California), EU (París), EU (Estocolmo), América del Sur (São Paulo) y Medio Oriente (Baréin)

La consola de AWS Amplify ofrece un servicio de alojamiento web estático completamente administrado que acelera el ciclo de lanzamiento de aplicaciones. Para ello, proporciona un flujo de trabajo de integración y entrega continuas a fin de crear e implementar aplicaciones web estáticas. Solo debe conectar el repositorio de código de la aplicación en la consola, y las modificaciones que se realicen en el frontend y el backend se implementarán en un único flujo de trabajo en cada confirmación de código.

AWS WAF now offers in-line regular expressions

AWS WAF extends its regular expression (regex) support, allowing regex patterns to be expressed in-line within a rule statement. Previously, you had to create a regex pattern set, which provides a collection of regex patterns in a rule statement, even if you wanted to use just a single regex pattern in your WAF rule logic. With in-line regex, you can now include a single regex pattern directly inside a WAF rule statement, simplifying how WAF rules are expressed within your web ACL.

Amazon Lex is now available in the Asia Pacific (Seoul) and Africa (Cape Town) regions

Starting today, Amazon Lex  is available in the Asia Pacific (Seoul) and Africa (Cape Town) regions. Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex combines advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text. This enables you to build applications with engaging users experiences and lifelike interactions. With Amazon Lex, you can easily create sophisticated, natural language, conversational bots (“chatbots”), virtual agents and IVR systems.

AWS Ground Station announces Licensing Accelerator

AWS is announcing Licensing Accelerator, a new AWS Ground Station feature which provides commercial businesses, space start-ups, and universities access to resources to help them more efficiently secure spectrum licenses required for their operations and missions. Licensing accelerator is free-of-charge to AWS Ground Station customers. AWS Ground Station is a fully managed service that lets customers control satellite communications, process satellite data, and scale their satellite operations. With Licensing Accelerator, AWS Ground Station customers can launch and scale their spacecraft operations faster by leveraging the latest, centrally located information about satellite licensing regulations such as space station licensing, remote sensing licenses, and International Telecommunications Union (ITU) coordination.

From Beginner to Machine Learning Instructor In A Year

Posted by Salim Abid, MENA Regional Lead, Developer Relations

Banner that reads Google Developer Student Clubs, Misr University for Science and Technology (MUST). Includes overhead image of person coding on a laptop

Yara Elkady, Google Developer Student Club (GDSC) Lead, can trace her passion for tech all the way back to a single moment. She was sitting in computer class when her middle school teacher posed a question to the class:

“Did you know that you can create apps and games like the ones that you spend so much time on?”

It was a simple question, but it was enough to plant the seed that would define the trajectory of Yara’s career. Following in the footsteps of so many beginners before her, Yara did a Google search to find out more about creating apps. She didn’t realize it at the time, but Yara had just taken her first steps down the path to becoming a developer.

Knowing that she wanted to pursue tech further, Yara went to college at Misr University for Science and Technology (MUST) in Giza, Egypt to study computer science. In her second year, she had begun reading more about artificial intelligence. Yara was blown away by the potential of training a machine to make decisions on its own. With machine learning, she could pursue more creative ideas that went beyond what was possible with traditional programming. As Yara explains, “It felt like magic”. Still, she felt lost like any beginner interested in AI.

Enter Google Developer Student Clubs

Yara first discovered the GDSC chapter at MUST through her school’s social media page. For the entirety of her second year, Yara attended workshops and saw firsthand how GDSC events could leave an impact on students aspiring to become developers. With help from Google Developer Student Clubs, Yara was able to grow her skills as a developer and connect with peers who shared her interests. At the end of the year, Yara applied to be a Lead so that she could help more students engage with the community. Not too long after, Yara was accepted as a GDSC Lead for the 2020-2021 season!

A classroom of people attend a GDSC MUST speaker session

A GDSC MUST speaker session

As part of becoming a GDSC Lead, Yara enrolled in the MENA DSC Leads Academy to receive hands-on training in various Google technologies. Despite being only the first time the Academy had ever been hosted (both in person and virtually), 100+ Leads from 150 GDSC chapters attended over the course of six weeks. Yara applied to the Machine Learning track and was chosen for the program. During the course, Yara mastered advanced machine learning concepts, including classical ML models, deep learning, data manipulation, and TensorFlow training. She also got to work with other Leads on advanced machine learning projects, helping her gain even more confidence in her ML knowledge.

Soon after passing the program, Yara collaborated with the GDSC Leads she met during the course to host a one-month ML track to pass on the knowledge they had learned to the GDSC community. Through the sessions she hosted, Yara was contacted by BambooGeeks, a startup that creates training opportunities for local tech aspirants to help them become industry-ready. Yara was offered a job as a machine learning instructor, and could now create sessions for the largest audience of trainees she’d ever worked with.

The road to certification

Yara didn’t realize it yet, but even more opportunities were headed her way. She learned from the GDSC MENA program manager that GDSC Leads would have the opportunity to take the TensorFlow Certification exam, if they wished to take it. It wouldn’t be easy, but Yara knew she had all the resources she needed to succeed. She wasted no time and created a study group with other GDSC Leads working to get certified. Together, Yara and her fellow Leads pulled endless all-nighters over the next few months so that they could skill up for the exam and support each other through the arduous study process. They also worked with Elyes Manai, a ML Google Developer Expert, who gave them an overview of the exam and recommended resources that would help them pass.

Thanks to those resources, support from her peers, and tons of hard work, Yara passed the exam and received her TensorFlow certification! And she wasn’t the only one. 11 other MENA GDSC Leads also passed the exam to receive their certifications. Yara and her study partners were the first women in Egypt to be featured in the TensorFlow Certificate Network, and Yara became one of 27 people in Africa to receive the TensorFlow Developer Certificate!

Image of Yara Elkady's TensorFlow Developer Certificate

Yara’s TensorFlow Developer Certificate

When Yara looks back at how she was able to fast track from beginner to certified machine learning developer in just a year, she credits Google Developer Student Clubs with:

  • Offering advanced Machine Learning training
  • Fostering connections with other Leads to host study jams
  • Providing guidance from machine learning GDEs
  • TensorFlow certification exam prep
  • Exposure to opportunities that enabled her to inspire others
  • Endless community support

The truth is, students like Yara make Google Developer Student Clubs special by sharing their knowledge with the community and building a support system with their peers that extends far beyond the classroom.

On the importance of community, Yara says it best:

“Reaching your goals is a much more enjoyable process when you have someone with you on the same journey, to share your ups and downs, and push you to do more when you feel like quitting. Your success becomes their success and that gives more meaning to your accomplishments.”

If you’re a student who is ready to join your own Google Developer Student Club community, find one near you here.