Description

Unlock the power of data-driven decision-making with our comprehensive course on “Artificial Intelligence and Machine Learning with KNIME Analytics.” KNIME Analytics is a powerful open-source platform that enables users to visually design data workflows, incorporating advanced analytics and machine learning techniques seamlessly. In this course, participants will embark on a journey to master the fundamentals of artificial intelligence and machine learning within the KNIME environment.

Through hands-on exercises and practical examples, learners will gain proficiency in data preprocessing, feature engineering, model training, and evaluation using KNIME’s intuitive interface. From classification and regression to clustering and text mining, this course covers a wide array of machine learning algorithms and techniques, empowering participants to extract valuable insights from their data.

Whether you’re a data scientist, business analyst, or decision-maker, this course equips you with the skills needed to harness the full potential of artificial intelligence and machine learning with KNIME Analytics, driving data-driven innovation and decision-making in your organization.

TABLE OF CONTENT

Unit 1: Introduction to AI/ML Basics

Overview of Artificial Intelligence (AI)
Introduction to Machine Learning (ML)
Key Concepts in AI and ML

Unit 2: Machine Learning Fundamentals

Types of Machine Learning (Supervised, Unsupervised, Reinforcement)
Data Preprocessing and Feature Engineering
Model Training and Evaluation

Unit 3: KNIME Analytics Platform

Introduction to KNIME
KNIME Workflow Basics
Data Import and Export in KNIME

Unit 4: KNIME Analytics – Data Manipulation

Data Wrangling in KNIME
Filtering and Transforming Data
Joining and Aggregating Data

Unit 5: KNIME Analytics – Model Building

Building Machine Learning Models in KNIME
Model Evaluation and Optimization
Deploying Models in KNIME

Unit 6: KNIME Analytics – Advanced Topics

Integration with External Data Sources
Automation and Batch Processing
Advanced Analytics and Reporting

Unit 7: AI/ML Applications

Real-world Applications of AI and ML
Case Studies and Use Cases
Ethical Considerations in AI/ML

Unit 8: Capstone Project in Artificial Intelligence with KNIME Analytics

Applying AI/ML and KNIME skills to a Real-world Project
Project Planning and Execution
Presentation of Capstone Projects

Please Visit Knime Official Site: || Locus Academy ha s more than a decade experience in delivering the training/staffing on Ansible and Puppet for DevOps Performance Optimization for corporates across the globe. The participants for the training/staffing on Ansible and Puppet for DevOps Performance Optimization are extremely satisfied and are able to implement the learnings in their on going projects.

Other useful references

Reference1

Reference2