5 Best Machine Learning Certifications and Courses
I have listed some courses below to help you set on your journey to becoming a great ML software engineers
1. IBM Introduction to Machine Learning Specialization
This course has a 4.8 rating on Coursera, and approximately 3K students have taken advantage of this. It is a program provided by IBM.This program is like a treasure chest that is packed with skills that will help you outshine others in this field. You'll see how ML algorithms may be used in a wide range of professional areas. You'll learn when to use machine learning approaches to tackle specific problems & when to use them to predict occurrences.
After completing the course, you will have obtained tangible ML abilities to employ in your company or job hunt, as well as a series of assets showcasing your competency.
Highlights of the course
- The course will take you roughly 3 months to complete if you add up all of the lectures.
- Because this is an intermediate-level course, having prior knowledge of ML will aid comprehension.
- This curriculum is entirely online, so you may study whenever you want.
What you will learn-
· What is regression, using SQL & ML architecture?
· How to determine the best ML strategy for your firm.
Link to the course- IBM Introduction to Machine Learning | Coursera
2. IBM Machine Learning Professional Certificate
Another great course available on the Coursera platform with an average 4.7 rating & over 12K learners enrolled. This course, as the name suggests is offered by IBM.
This curriculum comprises six modules that will provide you with
thorough conceptual knowledge & hands-on experience with the
key algorithms, applications, and best practices in Machine Learning.
You'll write your projects utilizing some of the most important
open-source toolkits as you go along.
Key highlights of the course
·
It will take about 6 months to go through the content of this training.
·
This intermediate course is ideal for anybody with basic computer
abilities, who are curious about exploiting information, & has a
desire for learning.
·
It is advised that you have some foundation in Python programming,
statistics, and linear algebra.
What you will learn-
·
Implementing ML methods & algorithms using python programming.
·
How to do regression analysis.
·
What are supervised & unsupervised ML regression.
Link to the course- IBM Machine Learning Professional Certificate | Coursera
3. Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate
It is one of the best courses accessible on the Coursera platform. This course, provided by Google Cloud, has a 4.6 average rating and over 11000 students have registered.
This program will not only aid you in obtaining and improving machine
learning abilities to bring value to your job, but it will also help you
prepare for the Google Cloud Professional ML certification.
Practical learning labs employing the Qwiklabs environment are included in
this professional certificate. These hands-on components will allow you to
put everything you've learned into practice. Qwiklabs uses Google Cloud
Platform solutions in their projects. With the principles discussed across
the sessions, you will obtain a virtual training experience.
Key highlights of the course
·
It is an intermediate-level program so, the learners are recommended to
have prior programming knowledge.
·
It will take you about 8 months to go through the content of this
course.
·
It is best suited for professional software developers or anyone curious to
learn how to implement ML practices.
What you will learn-
·
All the basics & abilities you will require to become successful as a
data scientist.
·
How to utilize google cloud tools to create & automate ML models to
address real-world problems.
·
All information about the professional Google cloud certificate like how
will it be helpful for you or what does it mean to have one.
Link to the course- Preparing for Google Cloud Certification: Machine Learning Engineer Professional
Certificate | Coursera
4. Amazon SageMaker: Simplifying Machine Learning Application Development
This course is available on the edX platform & is offered by AWS. Over 16K students have enrolled in this program to learn from AWS professionals to add ML to their software. ML is one of the highest desirable & trendiest fields of technology.
This program will teach you from the perspective of a software developer hence, helping in a better understanding of the topics & applying it to several practice exercises.
The lectures contain an introduction to ML & the challenges it may help resolve, how to use Jupyter Notebook to create a network based on SageMaker's built-in methods, & publishing the simulation tool using SageMaker.
Highlights of the course
· It will take about a month to cover all the lectures.
· Emphasize more on understanding the concepts instead of rushing to complete the course as it is completely online.
· AWS is the educational institution from where you will receive your training.
What you will learn-
· Using ML to confront & solve different queries.
· How to use SageMaker algorithms & Jupyter Notebook environment to create a network.
· Uploading a framework or model using SageMaker.
Link to the course- Amazon SageMaker: Simplifying Machine Learning Application Development | edX
5. AWS Certified Machine Learning Specialty 2024- Hands-On!
This course is offered on the Udemy website, where it has a 4.6 rating and has helped over 38K people. This program aims to teach you data modeling, SageMaker, & other skills that will help you in the AWS certification exam.
To ace this certification, you will need a solid understanding of AWS &
SageMaker, as well as a clear grasp of ML & the complexities of
feature engineering & model optimization that aren't typically
explained in textbooks or institutions.
Highlights of this course
·
The duration of this is about 11 hrs.
·
This course is accessible on mobile, pc, or smart TV.
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AWS account is required to perform lab exercises.
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Prior knowledge of ML will be appreciated.
What you will learn-
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Different feature engineering approaches.
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Applying advanced ML solutions.
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Implementing ML algorithms using the best security methods.
·
Tips about the AWS certification test.
Link to the course-
AWS Certified Machine Learning Specialty 2024 - Hands-On! | Udemy
Wrapping Up
You can swiftly build a solid foundation of ML & then apply them to applications. If you're seeking employment or a career boost, or just want to discover new things, these courses can aid you to reach that goal. This article illustrates some of the most well-known courses offered. Although the professional certifications for finishing the course may cost.
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