Posts from ‘product updates’


Security Concepts is an introductory security course, meant for those at the CCNA level. This 5 hour course is taught by Gabe Rivas and is a great prep course for those who are studying for the 210-260 IINS Exam.

About the Course

This course is the first of an 8 course CCNA Security Certification Curriculum.At INE, We believe that breaking the course up into smaller topics makes it easier to manage and digest your learning experience.

In this introductory course, we will walk you through basic security concepts that are meant to build a solid network security foundation and help you dive into more practical and advanced topics. We will start by helping you understand the meaning of Asset, Vulnerability, Threat, Risk, and Countermeasure terms. Then we will break down the CIA triad and show how it helps organizations develop sound security policies. We will also cover monitoring tools that assist in detecting events in real-time as well as cover concepts about common security zones. As we move forward, we will cover social engineering topics, network attacks, different kinds of malware found in today’s networks, data loss, cryptography and hashing, and finally we will go over common network topologies seen in a LAN, CAN, WAN, DC, and SOHO.


If this was a single course covering the entire CCNA Security blueprint, the pre-requisite would have been the CCENT certification or equivalent knowledge. Since this is just a subset of the CCNA Security blueprint, for this specific portion you only need to have basic network fundamentals knowledge and basic knowledge of infrastructure devices. There is nothing really complicated as a pre-requisite here.

Why You Should Watch

This course is great for anyone pursuing their CCNA Security certification. Regardless of certification achievement, some of the concepts covered in this course are useful to everyone that deals with computers and the more advanced concepts will be useful to anyone in the IT field, regardless of role (e.g. programmer, network designer, help desk technician). Security is not an aspect to take for granted and both, regular users and IT professionals, should have a bare minimum knowledge of common security practices.

Who Should Watch

Anyone interested in pursuing the CCNA Security certification or simply interested in gaining basic knowledge about network security.

About the Instructor

Gabe started his network engineer career in 2010 as a Co-Op at Cisco Systems in Herndon, VA. He landed a full-time position as a network consulting engineer and moved to Raleigh, NC where he worked at Cisco from 2011-2013. He then moved to a network support role working for ePlus Technology, a Cisco Gold Partner, from 2013-2016. Gabe is currently working at Cisco again, since 2016, as a test engineer and a professor of CCNA R&S, CCNA Security, and CCDA at Wake Technical Community College. Certifications that Gabe holds include: CCNA R&S, CCNA Security, CCNA Wireless, CCDA, CCNP R&S, and CCDP. Gabe is currently busy developing the CCNA Security course for INE and studying for his CCNP Security certification.


This course covers the basics of implementing inter-VLAN routing by explaining the theory behind two common methodologies, as well as their implementation on Cisco routers and switches. By the end of this course students will be able to explain the differences between “Router-On-A-Stick” and “Switched Virtual Interfaces,” as well as how to implement inter-VLAN routing using either of these techniques.

Why You Should Watch:

Virtually all organizations that implement VLANs into their switched networking topologies also need to know how to route IP traffic between those VLANs. Knowing the techniques available to accomplish this kind of routing is essential whether you are managing a network, or simply pursuing a networking certification (like the Cisco CCNA).

Many learners are confused about the differences between VLANs and SVIs (Switched Virtual Interfaces) as well as their inter-relationship. This course is meant to clarify any confusion you may have between those differences, and teach you both the theory and implementation (utilizing Cisco IOS software) of Inter-VLAN Routing.

Who Should Watch:

This course is intended for anyone wanting to learn about inter-VLAN routing with an emphasis on the techniques to do so using Cisco routers and switches. A basic familiarity with the Cisco IOS command line and the basic high-level concepts of VLANs, switches, routers and IP routing are recommended.

About The Instructor

Keith Bogart has been in the IT field since 1998. Keith started as a Customer Service Representative at Cisco Systems, and then transitioned into the Cisco Technical Assistance Center (TAC). For almost twenty years Keith has served as both a Technical Instructor as well as Course Developer for Cisco Systems and (for the past few years) INE. Keith is a Cisco Certified Internetwork Expert, as well as a Cisco Certified Networking Associate. Keith is currently employed as a Technical Instructor and Course Developer at INE.


This course is taught by Atindra Chaturvedi and is 6 hours and 38 minutes long. You view the video on our streaming site, or purchase it at

The VMware NSX 6.4 product release expands the capabilities of VMware in the Software Defined Data Center (SDDC) domain. This will be primarily a whiteboard discussion based course with some labs to set the context for the design discussion. Design aspects, limitations and good practice for the overlay network provided by NSX 6.4 will be covered. The latest advances in the data center network provided by Cisco with BGP EVPN and other technologies will be covered from the design perspective as an underlay for the NSX virtualized network. The course is geared to networking and virtualization professionals proficient at a CCNA or CCNP level of experience and knowledge.


Are you lost in a sea of AWS? Then get your head in the clouds with INE’s AWS Overview Course, brought to you by Peter and Geoff Douglas. This Video includes over 7 hours of content which will take you through every AWS service explaining the ins and outs of how you would use them.

This course it great for beginners or professionals. The Douglas brothers cover all of the services in AWS, walking you through overviews, deep dives and use cases. They also cover security and networking, the two essentials for getting up to speed, continuing through computing and storage. It doesn’t stop there, the course also covers topics like Big Data and the Internet of Things.

Join Peter and Geoff in a conversational look at all of the AWS services and you will walk away with a better understanding of all that Amazon has to offer. With over 30 years combined experience, these brothers will share their real word experience on AWS and other insights that will help you make more informed decisions when choosing cloud services.


This 6 hour course is designed for those that are preparing for the CISA exam. Expert instructor, Etienne Poeder, explains what to expect from this course, as well as who the course is designed for below:

The amount of effort required to ace this exam will depend on both your relevant knowledge and experience. Mere knowledge is insufficient for passing the exam because the exam doesn’t just test your familiarity with exam topics, but also your ability to actually apply your skills and education. An accounting/non-IS auditing background prior to this exam will likely work, but it is going to be more challenging with regard to your technical IT knowledge. As for the more techie professional, you will probably already understand the security and technology basics, but still need to show whether you understand the do’s and don’ts within auditing and related area’s in different types of organizations and architectures.

Whether you are an auditor or security professional, you can benefit from this course. I have done my best making sure we hit the ground running with the preparation for your exam. If you lack both the auditing as well as the technical knowledge/experience, this course will still benefit you, but it will be more challenging. You will need to prepare properly for the CISA exam to ace it. Of course, I will give you exam tips along the way and practical examples within the IT Audit security job practice to make studying a less bitter pill to swallow.

I will cover all 5 domains, which will summarize the most current information from the revised book according to the 2016 CISA Job Practice. This book is the most comprehensive peer-reviewed IS Audit, assurance, security and control resource available worldwide.

I have added assessment questions so you can test your knowledge and become more familiarized with the question types, structures and topics featured in the CISA exam. I have made a fine representative selection of questions, extracted from a 1,000 multiple-choice study exam that has previously appeared in the CISA Review Questions, Answers and Explained manual 2015 and the CISA Review Questions, Answers & Explanations Manual 2015 Supplement, both current and in accordance with the newly revised 2016 Job Practice.

So you want to be a professional auditor?

Go get your proper assistance for the CISA exam today!


East Coast, West Coast or International, we have a Bootcamp in a city near you! Check out our 2019 Bootcamp locations below, including a brand-new location; Salt Lake City, Utah.

Don’t see a city that works for you? We now offer online-live Bootcamp options as well. Check out our Bootcamps Site or contact a training advisor for more information.

Contact Us:, +1 877-224-8987, +1 775-826-4344 (international Customers)


This course is taught by Esteban Herrera and is 3hours and 28 minutes long. You can view the course here if you’re an All Access Pass member.

About The Course:

The Certificate of Cloud Security Knowledge (CCSK) certification is currently one of the most important cloud computing certifications you can get. The Cloud Security Knowledge Certification addresses core security concepts in cloud computing such as governance and enterprise risk management, compliance and audit management, infrastructure, virtualization & containers, data security & encryption, and much more. This course will be based on the documentation provided by Cloud Security Alliance.


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.


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.


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.


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.


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