AWS Certified Machine Learning - Specialty (MLS - C01) Certification Training

Amazon Sagemaker, Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more

Vimal Daga

The World Record Holder, Founder at LinuxWorld & #13, Sr. Principal IT Consultant, TEDx Speaker & Philanthropist

He has been featured at:

Who are Hiring

What will you learn in the training?

1.1 Create data repositories for machine learning.
● Identify data sources (e.g., content and location, primary sources such as user data)
● Determine storage mediums (e.g., DB, Data Lake, S3, EFS, EBS)
1.2 Identify and implement a data ingestion solution.
● Data job styles/types (batch load, streaming)
● Data ingestion pipelines (Batch-based ML workloads and streaming-based ML
○ Kinesis
○ Kinesis Analytics
○ Kinesis Firehose
○ Glue
● Job scheduling
1.3 Identify and implement a data transformation solution.
● Transforming data transit (ETL: Glue, EMR, AWS Batch)
● Handle ML-specific data using map reduce (Hadoop, Spark, Hive)

2.1 Sanitize and prepare data for modeling.
● Identify and handle missing data, corrupt data, stop words, etc.
● Formatting, normalizing, augmenting, and scaling data
● Labeled data (recognizing when you have enough labeled data and identifying
mitigation strategies [Data labeling tools (Mechanical Turk, manual labor)])
2.2 Perform feature engineering.
● Identify and extract features from data sets, including from data sources such as
text, speech, image, public datasets, etc.
● Analyze/evaluate feature engineering concepts (binning, tokenization, outliers,
synthetic features, 1 hot encoding, reducing dimensionality of data)
2.3 Analyze and visualize data for machine learning.
● Graphing (scatter plot, time series, histogram, box plot)
● Interpreting descriptive statistics (correlation, summary statistics, p value)
● Clustering (hierarchical, diagnosing, elbow plot, cluster size)

3.1 Frame business problems as machine learning problems.
● Determine when to use/when not to use ML
● Know the difference between supervised and unsupervised learning
● Selecting from among classification, regression, forecasting, clustering,
recommendation, etc.

3.2 Select the appropriate model(s) for a given machine learning problem.
● Xgboost, logistic regression, K-means, linear regression, decision trees, random
forests, RNN, CNN, Ensemble, Transfer learning
● Express intuition behind models
3.3 Train machine learning models.
● Train validation test split, cross-validation
● Optimizer, gradient descent, loss functions, local minima, convergence, batches,
probability, etc.
● Compute choice (GPU vs. CPU, distributed vs. non-distributed, platform [Spark vs.
● Model updates and retraining
○ Batch vs. real-time/online
3.4 Perform hyperparameter optimization.
● Regularization
○ Drop out
○ L1/L2
● Cross validation
● Model initialization
● Neural network architecture (layers/nodes), learning rate, activation functions
● Tree-based models (# of trees, # of levels)
● Linear models (learning rate)
3.5 Evaluate machine learning models.
● Avoid overfitting/underfitting (detect and handle bias and variance)
● Metrics (AUC-ROC, accuracy, precision, recall, RMSE, F1 score)
● Confusion matrix
● Offline and online model evaluation, A/B testing
● Compare models using metrics (time to train a model, quality of model, engineering
● Cross validation

4.1 Build machine learning solutions for performance, availability, scalability, resiliency, and
fault tolerance.
● AWS environment logging and monitoring
○ CloudTrail and CloudWatch
○ Build error monitoring Multiple regions,
● Multiple AZs
● AMI/golden image
● Docker containers
● Auto Scaling groups
● Rightsizing
○ Instances
○ Provisioned IOPS
○ Volumes
● Load balancing

● AWS best practices
4.2 Recommend and implement the appropriate machine learning services and features for
a given problem.
● ML on AWS (application services)
○ Poly
○ Lex
○ Transcribe
● AWS service limits
● Build your own model vs. SageMaker built-in algorithms
● Infrastructure: (spot, instance types), cost considerations
○ Using spot instances to train deep learning models using AWS Batch

4.3 Apply basic AWS security practices to machine learning solutions.
● S3 bucket policies
● Security groups
● Encryption/anonymization
4.4 Deploy and operationalize machine learning solutions.
● Exposing endpoints and interacting with them
● ML model versioning
● A/B testing
● Retrain pipelines
● ML debugging/troubleshooting
○ Detect and mitigate drop in performance
○ Monitor performance of the model

● Customer success stories and case studies using AWS Machine Learning
● Building recommendation systems with AWS Personalize
● Fraud detection and anomaly detection use cases
● Image and text classification applications

● Natural Language Processing (NLP) with AWS
● Introduction to AutoML and Automated Machine Learning
● Reinforcement learning advancements and applications
● Exploring AWS Machine Learning Roadmap and upcoming features

● Latest trends and developments in the field of Machine Learning
● Time series forecasting with AWS
● Anomaly detection and fraud detection with AWS

● Amazon Rekognition
● Amazon Comprehend
● Amazon Lex
● Amazon Polly
● Amazon Translate
● Amazon Transcribe
● Amazon Personalize
● Amazon Forecast
● Amazon DeepComposer
● Amazon Kendra
● Amazon Textract
● AWS DeepLens
● AWS DeepRacer

Who is this training for?

Working IT Professionals
Freshers aspiring for an IT role
College pursuing students
Data platform engineers/data architects
Data scientists
Managers & Team Leaders
Technical Co-Founders
College HOD & Professors
Data analysts
Solutions architects
Anyone willing to start & pursue career in Machine Learning domain

4 Reasons to learn AWS Machine Learning under Mr. Vimal Daga

Mr Vimal Daga Holds immense expertise in multitude of latest and high-end technologies that can power your career with growth, AWS being one of them. 

He is the One and Only mentor to Master 11 certification in just 11 days and a AWS & RedHat World Record Holder!


Teaching beyond the certification  


Practical Industry knowledge, Creator mentality


90 days technical support and a community for lifetime networking


Exclusive training of most demanded & market valued AWS technologies

Why AWS Certification is essential?

91% of AWS Certified IT professionals positive ROI
74% of IT companies increased their annual earnings
32% market share capture by AWS

You probably know this already! Right?

When certified, more than 80% of people identified a higher salary as an incentive to learn and pursue AWS certification.

Upto 30 Lpa – Salary range offered to beginners by giants like TCS, HCL, Wipro, and TechMahindra. 

AWS continues its dominance with 91% market share IaaS (Infrastructure-as-a-Service) globally.

88% – HRs prefer a certification while processing resumes – says an Open Source Jobs Report. 

74% AWS certified professionals increased their career opportunities & enhanced earning potential.

87% of hiring professionals prefer hiring hands-on learning candidates with AWS application skills. 

The national average salary for an AWS Specialist is ₹10,65,980 in India. 

According to Glassdoor The average annual salary for individuals with AWS skills who work as data scientists is about $103,000.

Our alumni works at:

Get Certified

Yes! You will be certified for this training once you submit the task given, if any

Official and verified:

Receive an instructor signed certificate with institution’s logo to verify your achievements and increase your job prospects

Easily shareable

Add the certificate to your CV or your Resume or post it directly on LInkedin. You can even post it on instagram and twitter.

Enhances Credibility

Use your certificate to enhance your professional credibility and stand out among your peers as an expert

Increase potential opportunities

By showcasing your achieved skill set using your certificate, attracting the employer for the desired job opportunities becomes easy

Know Your Mentor

None of the technologies is complex since created by human beings. Hence, anyone can learn it and create something new.

#13 proudly presents Vimal Daga as the mentor for this program

A world record holder, Mr. Vimal Daga is a Technologist, Philanthropist & A TEDx Speaker who is dedicatedly working atowards his vision- “Awakening the youth through a culture of right education”.

He is the first one in the world to become “RedHat Certified Architect Level 25 along with Enterprise Application Level 10”. Companies benefited from his 19+ years of experience.

He has expertise in multitude of latest and high-end technologies namely Machine Learning, Deep Learning, Delphix, AppDynamics, Docker, DevOps, Cloud Computing, AWS, and many more.
2,00,000+ Students Impacted
1,50,000+ Professionals trained
75+ Global Certifications
200+ Companies benefited

Vimal's Journey
From humble beginnings to winning learners' hearts across the globe

With the expertise to deliver any technology in an easy way and a heart to share his knowledge, Vimal Daga is a self-made IT enthusiast. He is meticulous about researching the skills needed for the future and making them available for the entrepreneurs & professionals of tomorrow. The masterly IT consultant has changed the lives of many students with his inspiring teachings.  You can be the next!

Stepping Stones of Vimal’s vision: 

Vimal Daga, in his near 20 years of experience has earned many laurels. To mention a few:
  • Became Young Entrepreneur 
  • A TedX speaker
  • Trained more than 3,50,000+ students for free
  • Two-time world record holder
  • Fastest achiever of 11 AWS global certifications (in 11 days)
  • Highest RHCA level holder (25th level with 10th level EA)
  • Creating 100s and more of entrepreneurs through his trainings

Book your spot ! We will be increasing the price soon…

AWS Certified Machine Learning – Specialty (Save ₹ 30,000)

₹ 15,000 ₹ 45,000 (+ taxes)

What you’ll learn...

And bonuses too...


Frequently Asked Questions

Time –  70 hours Total    

Live Session

Starting from 12th June, 2023

Certification Exam Preparation

The program will be delivered LIVE, providing full interactive opportunities to participants for sustainable learning.

No, we don’t provide any. But Yes, we do provide the access to the material which was covered in the training for your future reference

No, we are not offering any corporate or group discount.

We start from the very basics, so no previous knowledge is required.

Yes DEFINITELY..You will be added to a community where technical support team members will answer your queries for 60 days from the completion of the program.

We have a “no questions asked” 100% refund policy till 24 hours prior to the start of the program. After that, no refund will be entertained. Amount will be refunded within 7 days. For related queries email us at