SkillSoft Explore Course – Lambers, Inc.

Aspire Data Analyst to Data Scientist Data Science Track 2: Data Wrangler

This Aspire course explores the machine learning solutions provided by AWS (Amazon Web Services) and Microsoft, and how to compare the tools and frameworks that can be used to implement machine learning, and deep learning. You will learn to become efficient in data wrangling by building a foundation with data tools and technology. This course explores Machine Learning Toolkit provided by Microsoft, which provides various algorithms and applies artificial intelligence and deep learning. Learners will also examine Distributed Machine Learning Toolkit, which is hosted on Azure. Next, explore the machine learning tools provided by AWS, including DeepRacer and DeepLens which provide deep learning capabilities. You will learn how to use Amazon SageMaker, and how Jupyter notebooks are used to test machine learning algorithms. You will learn about other AWS tools, including TensorFlow, Apache MXNet, and Deep Learning AMI. Finally, learn about different tools for data mining and analytics, and how to build and process a data pipeline provided by KNIME (Konstanz Information Miner).

Asset ID	it_dsprtldj_02_enus
Course Type	Video Course
Course Category	Data Analyst to Data Scientist

Objectives
Data Tools: Machine Learning & Deep Learning in the Cloud Course Overview recognize the capabilities of Microsoft machine learning tools recognize the machine learning tools provided by AWS for data analysis specify Spark's machine leaning capabilities and the features of PySpark list frameworks that can be used to implement deep learning such as Keras, TensorFlow, Caffe, and PyTorch implement deep learning using Keras list tools that can be used to implement data mining and analytics and their features demonstrate the capabilities of building and processing data pipeline with Knime set up Keras, implement a deep learning algorithm, and build data pipelines using KNIME

Objectives

Data Tools: Machine Learning & Deep Learning in the Cloud

Course Overview
recognize the capabilities of Microsoft machine learning tools
recognize the machine learning tools provided by AWS for data analysis
specify Spark's machine leaning capabilities and the features of PySpark
list frameworks that can be used to implement deep learning such as Keras, TensorFlow, Caffe, and PyTorch
implement deep learning using Keras
list tools that can be used to implement data mining and analytics and their features
demonstrate the capabilities of building and processing data pipeline with Knime
set up Keras, implement a deep learning algorithm, and build data pipelines using KNIME