I passed the AWS Certified Machine Learning Speciality Exam on Monday. That makes my 10th AWS certification in the last 18 months.
The Machine Learning Specialty certification is unlike any of the other exams from AWS. The exam doesn’t just focus on AWS specifics but covers a wide range of Machine Learning topics. The exam blueprint provides a basis of this coverage.
The exam is probably the hardest of the 10 I’ve taken to date. The entire exam, I thought I know the material, but I don’t think I know it well enough to pass the exam. My score was good, and it satisfying to add this certification. For the Machine Learning exam, I put in well over 200 hours over the last six months and over 80 hours the four weeks before sitting the exam. Definitely think the Big Data Certification helped on the data preparation sections.
They’re a bunch of links I will share later this week, which I studied. In addition to all the reading, I did acloud.guru’s AWS Certified Machine Learning - Speciality, which provides 40% of the material required to pass the exam. The rest of the exam requires detailed knowledge of Machine Learning. I followed the learning track recommended by AWS for Data Scientist. I also did several sections from Linux Academy Machine Learning, including the great section explaining PCA. Lastly, I took the AWS practice exam. I did look at Whizlabs but was somewhat disappointed in their practice tests.
In 2020, I hope to get a project which will allow me to leverage Machine Learning in SageMaker to solve a complex customer problem.
I passed the AWS Certified Machine Learning Speciality Exam on Monday. That makes my 10th AWS certification in the last 18 months.
The Machine Learning Specialty certification is unlike any of the other exams from AWS. The exam doesn’t just focus on AWS specifics but covers a wide range of Machine Learning topics. The exam blueprint provides a basis of this coverage.
The exam is probably the hardest of the 10 I’ve taken to date. The entire exam, I thought I know the material, but I don’t think I know it well enough to pass the exam. My score was good, and it satisfying to add this certification. For the Machine Learning exam, I put in well over 200 hours over the last six months and over 80 hours the four weeks before sitting the exam. Definitely think the Big Data Certification helped on the data preparation sections.
They’re a bunch of links I will share later this week, which I studied. In addition to all the reading, I did acloud.guru’s AWS Certified Machine Learning - Speciality, which provides 40% of the material required to pass the exam. The rest of the exam requires detailed knowledge of Machine Learning. I followed the learning track recommended by AWS for Data Scientist. I also did several sections from Linux Academy Machine Learning, including the great section explaining PCA. Lastly, I took the AWS practice exam. I did look at Whizlabs but was somewhat disappointed in their practice tests.
In 2020, I hope to get a project which will allow me to leverage Machine Learning in SageMaker to solve a complex customer problem.
