AWS Machine Learning Certification Exam|2020 Complete Guide
What you'll learn
- Data Engineering
- Data types, Python Libraries (pandas, Numpy, scikit Learn, MatplotLib, Seaborn), data distributions, timeseries, Feature Engineering (imputation, binning, encoding, and normalization)
- AWS Services and Algorithms
- Amazon SageMaker, Amazon S3 Storage services, AWS Glue
- AWS Kinesis Services (Kinesis firehose, Kinesis video streams, Kinesis data streams, Kinesis analytics)
- Redshift, Redshift Spectrum, DynamoDB, Athena, Amazon Quicksight, Elastic Map Reduce (EMR)
- Rekognition, Lex, Polly, Comprehend, Translate, transcribe, BlazingText Word2Vec, DeepAR, Factorization Machines, Gradient Boosted Trees (XGBoost)
- Image Classification (ResNet), IP Insights, K-Means Clustering, K-Nearest Neighbor (k-NN)
- Latent Dirichlet Allocation (LDA), Linear Learner (Classification), Linear Learner (Regression)
- Neural Topic Modelling (NTM), Object2Vec, Object Detection, Principal Component Analysis (PCA), Random Cut Forest, Semantic Segmentation, and Seqence2Sequence
- Machine and Deep Learning Basics
Requirements
- Basic AI/ML/AWS knowledge
Description
Update 01/02/2020: Section #13 on Machine Learning Implementation and Operations is released.
Machine and Deep Learning are the hottest tech fields to master right now! Machine/Deep Learning techniques are widely adopted in many fields such as banking, healthcare, transportation and technology. Amazon has recently introduced the AWS machine Learning Certification Speciality exam and its quite challenging! AWS Certified Machine Learning Specialty is targeted at data scientists and developers who design, train and deploy AI/ML models to solve real-world challenging problems.
The bad news: this exam is a very challenging AWS exam since it tests the candidate’s knowledge on multiple aspects such as (1) Data Engineering and Feature Engineering, (2) AI/ML Models selection, (3) Appropriate AWS services solution to solve business problem, (4) AI/ML models building, training, and deployment, (5) Model optimization and Hyperparameters tuning. You need to answer these questions in order to pass the exam:
o How to select proper ML technique to solve a given business problem?
o Which AWS service could work best for a given problem?
o How to design, implement and scale secure ML solutions?
o How to choose the most cost-effective solution?
The good news: With over 500+ slides and over 50 practice questions, this course is by far the most comprehensive course on the market that provides students with the foundational knowledge to pass the AWS Machine Learning Certification exam like a pro! This course covers the most important concepts without any fillers or irrelevant information.
Who this course is for:
- Developers and data scientists wanting to get certified in AWS Machine Learning
Featured review
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Course content
- Preview04:57
- Preview09:05
- Preview10:13
- 00:32BONUS: Learning Path
- Preview03:02
- Preview06:25
- 2 questionsSection Introduction Quiz
- Preview09:48
- 2 questionsWhat is Machine Learning and AI - Part 1 Quiz
- 09:50What is Machine Learning and AI - Part 2
- 2 questionsWhat is Machine Learning and AI - Part 2 Quiz
- Preview06:24
- 2 questionsAmazon Web Services Quiz
- 14:04AIML Data Lingo - Labeled vs. unlabeled
- 2 questionsAIML Data Lingo - Labeled vs. unlabeled Quiz
- 10:04AIML Data Lingo - Data Types
- 2 questionsAIML Data Lingo - Data Types - quiz
- 06:50Database vs. datalake vs. warehouse
- 2 questionsDatabase vs. datalake vs. warehouse - Quiz
- 11:02AWS Storage S3 DynamoDB RDS
- 2 questionsAWS Storage S3 DynamoDB RDS Quiz
- 00:10GET YOUR BONUS MATERIALS
- 00:02Section 1 Slides
Instructors
- 4.5 Instructor Rating
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Ryan Ahmed is a best-selling Udemy instructor who is passionate about education and technology. Ryan's mission is to make quality education accessible and affordable to everyone. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business.
Ryan held several engineering positions at Fortune 500 companies globally such as Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. Ryan has taught several courses on Science, Technology, Engineering and Mathematics to over 100,000+ students globally. He has over 15 published journal and conference research papers on state estimation, AI, Machine learning, battery modeling and EV controls. He is the co-recipient of the best paper award at the IEEE Transportation Electrification Conference and Expo (iTEC 2012) in Detroit, MI, USA.
Ryan is a Stanford Certified Project Manager (SCPM), certified Professional Engineer (P.Eng.) in Ontario, a member of the Society of Automotive Engineers (SAE), and a member of the Institute of Electrical and Electronics Engineers (IEEE). He is also the program Co-Chair at the 2017 IEEE Transportation and Electrification Conference (iTEC’17) in Chicago, IL, USA.
* McMaster University is one of only four Canadian universities consistently ranked in the top 100 in the world.
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My name is Kirill Eremenko and I am super-psyched that you are reading this!
Professionally, I am a Data Science management consultant with over five years of experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and today I leverage Big Data to drive business strategy, revamp customer experience and revolutionize existing operational processes.
From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. I am also passionate about public speaking, and regularly present on Big Data at leading Australian universities and industry events.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!
- 4.5 Instructor Rating
- 248,048 Reviews
- 1,168,018 Students
- 82 Courses
Hadelin is the co-founder and CEO at BlueLife AI, which leverages the power of cutting edge Artificial Intelligence to empower businesses to make massive profits by innovating, automating processes and maximizing efficiency. Hadelin is also an online entrepreneur who has created 70+ top-rated educational e-courses to the world on topics such as Machine Learning, Deep Learning, Artificial Intelligence and Blockchain, which have reached 1M+ students in 210 countries.
- 4.5 Instructor Rating
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Hi there,
We are the SuperDataScience Social team. You will be hearing from us when new SDS courses are released, when we publish new podcasts, blogs, share cheatsheets and more!
We are here to help you stay on the cutting edge of Data Science and Technology.
See you in class,
Sincerely,
The Real People at SuperDataScience
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Mitch is a Canadian filmmaker from Harrow Ontario, Canada. In 2016 he graduated from Dakota State University with a B.S, in Computer Graphics specializing in Film and Cinematic Arts.
Currently, Mitch operates as the Chairman of Red Cape Studios, Inc. where he continues his passion for filmmaking. He is also the Host of Red Cape Learning and Produces / Directs content for Red Cape Films.
He has reached over 340,000 + Students on Udemy and Produced more than 3X Best-Selling Courses.
Mitch is currently working Producing Online Educational Courses thru Red Cape Studios Inc.
Winning several awards at Dakota State University such as "1st Place BeadleMania", "Winner College 10th Anniversary Dordt Film Festival" as well as "Outstanding Artist Award College of Arts and Sciences".
Mitch has been Featured on CBC's "Windsors Shorts" Tv Show and was also the Producer/Director for TEDX Windsor, featuring speakers from across the Country.