Amazon SageMaker Studio for Data Scientists Training in Germany
Build, train, and deploy ML models using SageMaker Studio
Attain practical experience in data processing & model training
Learn from experienced industry trainers
Master skills from data wrangling to model tuning
Acquire job-ready skills for advanced data science roles
Flexible, focused, & career-oriented training
Easy and convenient payment options available
4.78/56987 EnrolledEnrolled Learners
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Overview
What our training includes
- Provides skills to build scalable ML workflows through SageMaker Studio
- Prepares candidates for data tasks using AWS Glue & Data Wrangler
- Trains users to refine models using SageMaker Experiments effectively
- Explains bias checks & ML automation using SageMaker Autopilot
- Delivers tools for model management with SageMaker Pipelines
- Teaches optimization using SageMaker Debugger in practical sessions
Upcoming sessions
Curriculum
1
JupyterLab Extensions in SageMaker Studio
2
Demonstration: SageMaker user interface demo
1
Using SageMaker Data Wrangler for data processing
2
Hands-On Lab: Analyze and prepare data using Amazon SageMaker Data Wrangler
3
Using Amazon EMR
4
Hands-On Lab: Analyze and prepare data at scale using Amazon EMR
5
Using AWS Glue interactive sessions
6
Using SageMaker Processing with custom scripts
7
Hands-On Lab: Data processing using Amazon SageMaker Processing and SageMaker
8
Python SDK
9
SageMaker Feature Store
10
Hands-On Lab: Feature engineering using SageMaker Feature Store
1
SageMaker training jobs
2
Built-in algorithms
3
Bring your own script
4
Bring your own container
5
SageMaker Experiments
6
Hands-On Lab: Using SageMaker Experiments to Track Iterations of Training and Tuning
7
SageMaker Debugger
8
Hands-On Lab: Analyzing, Detecting, and Setting Alerts Using SageMaker Debugger
9
Automatic model tuning
10
SageMaker Autopilot: Automated ML
11
Demonstration: SageMaker Autopilot
12
Bias detection
13
Hands-On Lab: Using SageMaker Clarify for Bias and Explainability
14
SageMaker Jumpstart
1
SageMaker Model Registry
2
SageMaker Pipelines
3
Hands-On Lab: Using SageMaker Pipelines and SageMaker Model Registry with SageMaker
4
Studio
5
SageMaker model inference options
6
Scaling
7
Testing strategies, performance, and optimization
8
Hands-On Lab: Inferencing with SageMaker Studio
1
Amazon SageMaker Model Monitor
2
Discussion: Case study
3
Demonstration: Model Monitoring
1
Accrued cost and shutting down
2
Updates
1
Environment setup
2
Challenge 1: Analyze and prepare the dataset with SageMaker Data Wrangler
3
Challenge 2: Create feature groups in SageMaker Feature Store
4
Challenge 3: Perform and manage model training and tuning using SageMaker Experiments
5
(Optional) Challenge 4: Use SageMaker Debugger for training performance and model
6
optimization
7
Challenge 5: Evaluate the model for bias using SageMaker Clarify
8
Challenge 6: Perform batch predictions using model endpoint
9
(Optional) Challenge 7: Automate full model development process using SageMaker Pipeline
Meet your Trainer
Our Trainers
Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.
We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.
Learning Outcomes
Upon finishing the training, you will:
1
Master data handling through Data Wrangler and AWS Glue
2
Boost training efficiency with real-time insights from SageMaker Debugger
3
Streamline machine learning tasks using Autopilot and Pipelines
4
Manage model deployment and updates via Model Registry
5
Promote fairness in AI by detecting bias with SageMaker Clarify
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
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Frequently asked questions
The Amazon Sagemaker Studio for Data Scientists Training in Germany is designed to teach professionals Amazon SageMaker Studio for Machine Learning. You learn to build, train, monitor, and deploy machine learning models using Amazon SageMaker Studio tools. This training will also provide practical lab work and actual challenges for better learning.
This training will be beneficial for professionals working with ML -
- Data scientists
- Machine learning engineers
- Developers looking to implement end-to-end ML pipelines
- Cloud professionals who want to integrate ML with AWS services
- AI/ML team leads
- AI/ML project managers
Our training is available in several different modes for convenient learning. These include -
- Instructor-led group sessions
- Personalized one-on-one training
- Live interactive online classes
Our Amazon Sagemaker Studio for Data Scientists Certification in Germany is divided into several modules with practical labs, covering the following activities and sessions -
- Data preparation using SageMaker Data Wrangler
- Feature engineering with SageMaker Feature Store
- Model training and tuning using SageMaker Experiments
- Bias detection with SageMaker Clarify
- Full automation with SageMaker Pipelines
This Amazon Sagemaker Studio for Data Scientists Training teaches model deployment through -
- SageMaker Pipelines for CI/CD workflows
- Model version control through SageMaker Model Registry
- Hands-on experience with real-time and batch inference options
Do you want to learn more about Learners Point Academy?
- Learn more about courses
- Understand about our methodology
- Let’s talk about Corporate trainings
- Anything else that you want to know, we are here for you!
