Author Archive

Jul
20






Data Science in the Cloud

Data Science, machine learning, deep learning; these are the different driving forces of the current revolution which is changing the way businesses, companies and people make decisions, work and innovate. Data Science is triggering profound innovations in healthcare, finance, transportation, manufacturing and many other sectors.

Data science is evolving at lightning speed with a multiplication of approaches, tools and platforms. In parallel to script-based data science, think python and scikit-learn, the major cloud providers are developing platforms to power and facilitate the data scientist’s daily work and the implementation of data science projects in production. The Google Cloud Platform offers one of the most innovative and user friendly data science ecosystem.

My name is Alexis Perrier, I am a data science consultant and I’m very excited to be the instructor on this data science course on the google cloud platform. I teach data science in colleges, bootcamps and also for company training sessions. I recently wrote a couple of books on Machine Learning on the Google Cloud Platform and on AWS, both are with Packt Publishing.

I have a PhD in signal processing from Telecom-ParisTech followed by over 20 years in software engineering and 5 years ago I went back to data science. Although the data science ecosystem is fast evolving, it is deeply grounded in solid applied mathematics. Case in point, in the mid 90s, my signal processing PhD was on echo cancellation in hands-free phones and for that we were already working with the stochastic gradient algorithm which is widely used now days to train deep learning networks.

In 2015, Google released Tensorflow which is now the most popular deep learning framework. And in recent years Google has launched several high performing services across the whole data science workflow: from data storage with Google Storage and BigQuery, distributed computing with the Google Compute Engine, specific Deep Learning APIs for text, images, videos and speech and the Google Machine Learning Engine dedicated to training deep learning models.


Learning Outcomes

In this course, you will focus on the cloud infrastructure, data storage, and machine learning services of the google cloud platform.

At the end of this course you will be able to:

  • Launch your own Compute Engine instances and build a data science stack running Jupyter notebooks
  • Use advanced features of Google Storage such as synchronization, access control lists, signed urls and others
  • Host and query your data in BigQuery which is google’s data warehouse solution
  • Launch Datalab instances to work collaboratively in Jupyter notebooks using data from BigQuery and other sources
  • Use Google Deep learning APIs to extract information from text, images, videos and speech
  • Use Google ml-engine to rapidly train tensorflow models in the cloud without having to configure virtual instances

Throughout the course we will work with the Google SDK command lines in the terminal and develop simple python scripts to interact with the google services.

I’ve created this course with the following objectives:

  • To enable you to leverage the powerful google infrastructure for all your data science projects
  • To demonstrate some of the limitations of these google services
  • To make sure that the important implementation details stand out from the overall technical documentation
  • To reflect real-world scenarios as much as possible by using non-trivial datasets whenever possible


Course Requirements

This course is intended for data scientists of all levels who want to get a full understanding as well as hands-on practice of the Google Cloud Platform services for data science projects.

You should be familiar with the overall concepts in data science but more importantly have some minimal experience with Python scripting, sql queries, Shell commands. Nothing we do in this course requires deep knowledge of Shell or Python scripts, but being comfortable working from the terminal will help.

All the Shell and scripts in the videos are available on this github repository.

Conclusion

The Google Cloud Platform offers a very powerful set of services for data science. And in my personal experience it is quite a user-friendly environment to work with. Since most services are server-less you are able to leverage the amazing power of the google cloud infrastructure without the pain of setting up, launching and scaling servers manually or programmatically.

Google Cloud is a fast evolving ecosystem with periodic updates, and frequent alpha and beta releases of new features and services. Mastering these google services will definitely boost your data science knowledge and skills.

Please feel free to drop me a line if you have any question or comments.

Jul
19

Rohit has been in the networking industry for more than 17 years, with a focus on Cisco networking for the past 15 years. Rohit not only brings his years of teaching experience to the classroom, but also years of real-world enterprise and service provider experience. Rohit has assisted hundreds of engineers in obtaining their CCIE certification, and has been conducting CCIE RS, CCIE SEC, CCIE SP and CCIE Collaboration for Cisco Systems worldwide. Rohit currently holds 5xCCIE’s (Routing Switching, Service Provider, Security, Voice and Collaboration). When not teaching or developing new products, Rohit consults with large ISPs and enterprise customers in India and UK. Rohit is currently pursuing his CCIE Data Center certification.

Jul
17

This course covers the basics of Docker and Kubernetes by showing how to build modern clouds with these technologies. By the end of this course students will be able to launch a Kubernetes cluster and deploy self-healing and scalable applications, as well as create their own continuous integration, and continuous delivery pipeline.



Why You Should Watch:

Kubernetes has quickly become the standard platform for running containerized workloads. All the major public clouds now have a Kubernetes-as-a-Service offering and popular container management tools, like Rancher, have migrated their underlying platform from in-house software, like Cattle, to Kubernetes. Even Docker themselves are now natively supporting Kubernetes.

This course is meant to teach you how to get started building modern clouds with Kubernetes and Docker, while covering the basic concepts of DevOps.


Who Should Watch:

This course is intended for anyone wanting to learn about Kubernetes and Docker. A basic familiarity with the Linux command line and the basic high-level concepts of the public cloud are recommended. The recommended public cloud platform for this course is Google Cloud Platform.


About The Instructor

David Coronel has been in the IT field since 2002. David started as a call center agent and quickly made his way to systems administration. David is a Certified Kubernetes Administrator, a Docker Certified Associate, a Certified OpenStack Administrator as well as an AWS Certified Solutions Architect Associate. David is currently employed as a Technical Account Manager at Canonical, the company behind Ubuntu.

Jul
13

This is a 2 and a half hour introductory course in Machine Learning. It’s taught by Yogesh Kulkarni, a practitioner and instructor in the field of Machine learning.


Why You Should Study This Topic:

Machine Learning is getting more popular each day. It is not just hype, but an essential technique made possible and powerful by the availability of data. Studying Machine Learning is imperative, and Python is a good programming environment to get started with the basics. This workshop will not only familiarize you with this powerful and popular techniques, but will also give you the confidence necessary to venture into this on your own, thereby improving your chances of a lucrative career ahead.


Who Should Watch:

This course is for anyone who wants to become more familiar with Machine Learning. It is recommended to have some knowledge of college level mathematics and programming using Python. You can be from any domain, such as Finance, Engineering, Agriculture, Biology, etc. you will know a new problem-solving technique which could be of great help in your own domain.


What You’ll Learn:

You will learn what Artificial Intelligence is, how it relates to Machine Learning and Deep Learning, what’s the core idea behind problem solving and how Machine Learning technique goes about finding solutions. You will also learn how Machine Learning solutions are implemented using Python programming and see an example a practical real-life case.


About The Instructor:

Yogesh H. Kulkarni is a consultant and an instructor in Data Science space, with a doctoral degree in Mechanical Engineering, specializing in Geometric Modeling algorithms. He has taught Python, Machine Learning and Natural Language processing in the corporate world as well as to students in Engineering colleges.

Jul
12

According to the 2018 CIO Survey many organizations are having trouble finding and retaining talent with the necessary skillset to fill positions related to some of today’s most popular and cutting edge technologies. Organizations point to education program’s inability to keep up with rapid changes in modern technology, as well as a general high demand for certain positions as the culprit (Florentine).

Luckily, at INE we add new courses every week on a variety of topics, including those that are considered among the newest and most cutting-edge. Continue Reading to see which IT jobs the CIO report has dubbed the highest in-demand.

This blog post is based off of an original CIO article by Sharon Florentine. To read the original article click here.

Jul
09

This course was created by Piotr Kaluzny and is 2 hours and 32 minutes long. It consists of multiple videos where the Instructor discusses all relevant theoretical concepts and technologies, (in-depth explanations, whiteboarding) and shows how to implement them on the current CCIE Security v5 lab exam hardware.




Why You Should Watch:

Security is no longer just an “important” component of an organization. A constantly-increasing number of aggressive cyber criminals launch their attacks not only from the outside, but also inside of the organization, making security an inherent component of any modern network/system design.

This course, like all other courses that are part of the “CCIE Security v5 Technologies” series, is meant to teach you Cisco security technologies and solutions using the latest industry best practices to secure systems and environments against modern security risks, threats, vulnerabilities, and requirements.


Who Should Watch:

This course is not only intended for students preparing to the current CCNA/CCNP/CCIE Security exam, but also for experienced Network (Security) Engineers or Administrators looking to refresh their knowledge on important Network Security concepts before moving forward with other certifications.


What You’ll Learn:

By completing this course, you will understand and learn about the different Layer 2 attacks and mitigation techniques, such as attacks on STP and switching infrastructure, Dynamic ARP Inspection, DHCP Snooping, IP Source Guard, Storm Control, Private VLANs or Protocol Storm Protection.


About the Instructor

Piotr Kaluzny has been in the IT field since 2002 when he was exposed to networking and programming during his studies. His career in production networks began in 2007, right after graduating with MSc in Computer Science. Piotr quickly progressed his career by working for multiple enterprise and non-enterprise companies in different Routing and Switching and Security roles, with his responsibilities ranging from operations and engineering to consulting and management.



Since the very beginning Piotr has been heavily focused on the Security track to finally prove his skills in 2009 by passing the CCIE Security certification exam (#25565) in the first attempt (he also holds R&S and Security CCNP and CCNA certifications).



Piotr already has an extensive background as a Senior Technical Instructor. For the past several years he has been solely responsible for designing, developing and conducting CCNA, CCNP and CCIE training courses for one of the largest and most respected Cisco training company in the world.

Jul
06



CCIE Routing & Switching:


Online Graded Practice Lab

January 2-4
April 15-18
April 16-19
May 28-31


5 Day Bootcamp

January 7-11


Written Exam Bootcamp

January 7-11
April 15-19
June 24-28


Lab Exam Bootcamp

January 28 – February 3
February 4-10
February 25 – March 3
March 25-31
May 13-19
June 10-16
June 24-30



CCIE Security:


5 Day Bootcamp

January 7-11


Written Exam Bootcamp

January 14-18
March 25-29


Lab Exam Bootcamp

January 21-27
February 25 – March 3
April 1-7
June 17-23



CCIE Data Center:


Lab Exam Bootcamp

January 7-13
February 4-10
March 18-24
April 29 – May 5
June 17-23



CCIE Service Provider:


Lab Exam Bootcamp

March 18-24
June 3-9



CCIE Collaboration:


Lab Exam Bootcamp

January 28 – February 3
March 4-10
April 8-14



CCNP Routing & Switching:


7 Day Bootcamp

January 28 – February 3
February 11-15
March 11-17
April 29 – May 5
May 13-17



CCNA Routing & Switching:


5 Day Bootcamp

February 25 – March 1
April 15-19
June 10-14



CCNA Security:


5 Day Bootcamp

April 1-5
June 24-28

Visit our Bootcamps Site to purchase your course today!

Jul
05

We’ve just added a new Network Automation course, Network Automation with Ansible (v2), to our video library!



Instructor: Eric Chou

Course Duration: 4hrs 33min


Course Description

Ansible is quickly becoming the automation tool of choice for networking. This course aims to demystify Ansible and get you up and running with today’s technologies. After covering the basics, we’ll move on to the more advanced topics as they are applicable to network automation. This course will be cover the latest Ansible GA release 2.4 with some augments for upcoming development release 2.5.

Jul
03


Contact a Training Specialist at info@ine.com, or give us a call at +1-877-224-8987 or +1-775-826-4344 (outside the U.S.) for more information.

Jun
29

Our Newest Juniper course, Juniper Security (JSEC) Technology is now live! Whether you’re preparing for your Juniper Specialist Exam, or just looking to brush up on Juniper SRX Devices, this course is an excellent resource for IT security professionals. Tune in for 3 hours of instruction with Juniper expert Mauricio Spinelli by logging into your members account here.



Why You Should Watch:

Juniper networks are growing more each day and helping companies move forward to cloud technologies using SDN and NFV. One of the most important matters to focus on nowadays is security. Studying security matters of Juniper networks will help you move forward in your career and achieve your Juniper Security Specialist certification without any issues.

Who Should Watch:

This course is designed for network and security engineers with basic or intermediate levels of security knowledge who are looking to improve their skills.

What You’ll Learn:

This course will help you improve security skills, with a focus on Juniper technologies. In this course you will learn how to manage, deploy and troubleshoot security issues, such as VPN problems and deploys.

About The Instructor:

Mauricio Spinelli is a Network and Security engineer with more than 7 years of experience in the field dedicated to designing new infrastructures and solving complex issues in many market segments. Mauricio has several certifications in Juniper, such as JNCI and JNCIP-Security.

Categories

CCIE Bloggers