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CENGN Academy Free Training For Students

CENGN Academy

Applications have officially closed! Thank you to everyone who applied. Successful candidates will be notified. Keep an eye on your inbox!

As COVID-19 continues to linger, students have taken a direct hit to their educations and ability to find work.

This July, CENGN is offering a selection of 2 different courses (valued at $ 2,600 each) to 40 students from an ICT-related university or college program in Canada, free of charge. Whether at university or college, these 40 students will have free access to their chosen CENGN Academy course. After completing the course, students can take the digital badge exam. Those who pass can post their credentials on LinkedIn, indicating that they are qualified and ready to work.

Docker and Kubernetes BasicsMachine Learning with Python
Docker and Kubernetes Machine Learning with Python
Apply By: June 26, 2022
Applications Closes
Apply By: June 26, 2022
Applications Closed
Start Date: July 4, 2022Start Date: July 4, 2022

Course Objectives:
After taking this course, you will be able to:

-Explain key container concepts

-Compare virtual machines and containers

-Manage Docker containers via Docker Hub

-Modify a running Docker container and commit changes

-Describe Kubernetes components such as pods, worker nodes and master nodes

-Create a single-node Kubernetes cluster

-Define standard Kubernetes objects using manifest files

-Use Kubernetes labels and selectors to group objects and organize clusters

-Troubleshoot Kubernetes manifest files

Course Objectives:
After taking this course, you will be able to:

-Recognize the key concepts, best practices, and applications of machine learning

-Identify the most widely used machine learning algorithms and discuss their strengths and weaknesses.

-Describe basic machine learning principles such as classification, regression, clustering, association learning, and dimensionality reduction.

-Recall Python fundamentals, including basic syntax, variables, and types.

-Build, train, and evaluate the performance of machine learning models using Python and its associated libraries.

-Select the appropriate machine learning model for a given problem.

-Perform exploratory data analysis on a dataset to detect anomalies and summarize its main characteristics.


Recommendation

If you’re new to Cloud and DevOps, we recommend Docker & Kubernetes Basics.		Recommendation

If you’re interested in programming and data science, we recommend Machine Learning with Python.
Suggested for Students Interested in Becoming:

-A Software Engineer or Architect

-A Network Engineer or Architect

-A Cloud Engineer or Architect

-A Cloud Team Manager		Suggested for Students Interested in Becoming:

-A Software developer/engineer/architect starting with ML

-A Software team lead or manager overseeing ML teams
Hours Needed to Complete the Course
20-25		Hours Needed to Complete the Course
20-25
Delivery Mode
Learn on your own schedule with self-paced online training and labs
*End date for access: August 2, 2022		Delivery Mode
Learn on your own schedule with self-paced online training and labs
*End date for access: August 2, 2022
Applications ClosedApplications Closed
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