Data Science with KNIME Analytics Platform Training Course

Course Code

knimeanalytics

Duration

21 hours (usually 3 days including breaks)

Requirements

Recommended

  • A basic understanding of making sense of the data.
  • Experience with fundamental data processing.

Audience

  • data analysts
  • data scientists
  • business analysts

Overview

KNIME Analytics Platform is a leading open source option for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst.

This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows

This instructor-led, live training (onsite or remote) is aimed at data professionals who wish to use KNIME to solve complex business needs.

It is targeted for the audience that doesnt know programming and intends to use cutting edge tools to implement analytics scenarios

By the end of this training, participants will be able to:

  • Install and configure KNIME.
  • Build Data Science scenarios
  • Train, test and validate models
  • Implement end to end value chain of data science models

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course or to know more on this program, please contact us to arrange.

Course Outline

Day 1:

Module 1: KNIME Analytics Platform: Overview

  • Installation
  • Starting and customizing KNIME Analytics Platform
  • Nodes, data and workflows
  • The data science cycle

Module 2: Data Access

  • Read Data from file
  • Accessing REST Services

Module 3: ETL and Data Manipulation

  • Row & Column filtering
  • Aggregators
  • Join & Concatenation
  • Transformation: Conversion, Replacement, Standardization, and New Feature Generation
  • Data Preparation for Time Series Analysis

Day 2:

Module 4: Exporting Data

  • Write to a file
  • Generating a Report

Module 5: Data Visualization

  • Interactive Univariate Visual Exploration
  • Interactive Multivariate Visual Exploration
  • Advanced Visualization Features
     

Module 6: Predictive Analytics using KNIME

  • Data Mining Basic Concepts
  • Regressions
  • Decision Tree Family
  • Model Evaluation

Day 3:

Module 7: Controlling the flow

  • Workflow Parameterization: Flow Variables
  • Re-executing Workflow Parts: Loops
  • Cleaning up your Workflow

Module 8: Hands on KNIME Analytics Platform based Case Study
 

Testimonials

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★★★★★

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