Asphalt

Process Optimization Analyst

The Process Optimization Analyst in the asphalt industry is responsible for leveraging data to enhance and  optimize various stages of the production process.

This role focuses on analyzing data, improving operational  efficiency, and implementing advanced machine learning models to support decision-making and process  improvements for example Root Cause Analysis.

All training courses

Training courses by skill

Predictive Analytics Training RapidMiner for Machine Learning and Predictive Analytics Training Course

This instructor-led course on RapidMiner offers a comprehensive introduction to using this open-source data science platform for data preparation, machine learning, and predictive analytics. Participants will gain hands-on experience with RapidMiner Studio, learning to develop, validate, and deploy predictive models efficiently. The course is designed for data scientists, engineers, and developers looking to enhance their skills in data-driven decision-making and analytics.

Provider
NobleProg
Target
  • Data Scientists/Analysts
  • Engineers
  • Developers
Sector
  • Automotive
  • Aerospace
  • Agriculture
  • Chemical
  • Computer - Software
  • Construction
  • Education
  • Research & Development
  • Energy
Area
Artificial Intelligence
Method
Online/Classroom
Duration
14 Hours
Cost
2580 PLN
Contact
warszawa@nobleprog.pl
Date
Periodic and always available
Location
Online

Learning Outcomes

  • Install and Configure RapidMiner: Set up and customize RapidMiner for optimal use
  • Prepare and Visualize Data: Clean and visualize data within RapidMiner for effective analysis
  • Validate Machine Learning Models: Ensure the accuracy and reliability of predictive models
  • Create and Deploy Predictive Models: Mashup data and operationalize predictive analytics within business processes
  • Troubleshoot and Optimize: Resolve issues and fine-tune RapidMiner for enhanced performance
Learn More

Data Science Databases and SQL for Data Science with Python

In this course, you will learn to analyze data within a database using SQL and Python, create a relational database and work with multiple tables using DDL commands, construct basic to intermediate-level SQL queries using DML commands, and compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures, and joins.

Provider
Coursera
Target
  • Directors
  • Plant Managers
  • Engineers
Sector
  • Automotive
  • Aerospace
  • Agriculture
  • Chemical
  • Computer - Software
  • Construction
  • Education
  • Research & Development
  • Energy
Area
Data Science and Programming
Method
Webinar/Online
Duration
20 Hours
Cost
Free
Date
Ongoing
Location
Online

Learning Outcomes

  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
Learn More

Data Management Introduction to Big Data with Spark and Hadoop

This course offers a comprehensive introduction to big data concepts, tools, and technologies, with a focus on practical applications in modern data processing. Participants will explore the impact of big data on industries, understand the Apache Hadoop ecosystem, and dive deep into Spark programming for large-scale data handling. The course emphasizes hands-on learning, from basic parallel programming to advanced Spark optimizations, preparing learners to integrate big data solutions effectively within real-world environments.

Provider
Coursera
Target
  • Data Analysts
  • Directors
  • Plant Managers
  • Engineers
Sector
  • Automotive
  • Aerospace
  • Agriculture
  • Chemical
  • Computer - Software
  • Construction
  • Education
  • Research & Development
  • Energy
Area
IT
Method
Webinar/Online
Duration
18 Hours
Cost
Free
Date
Ongoing
Location
Online

Learning Outcomes

  • Understand the Impact of Big Data: Analyze key use cases, tools, and processing methods used in big data management
  • Describe Apache Hadoop Ecosystem: Explain Hadoop architecture and work with its core components, including Hive, HDFS, HBase, Spark, and MapReduce
  • Apply Spark Programming: Develop basic parallel programming skills using DataFrames, datasets, and Spark SQL
  • Optimize Spark Operations: Use Spark’s RDDs and datasets, optimize Spark SQL with Catalyst and Tungsten, and explore Spark’s development and runtime options
Learn More
Predictive models in industrial applications
Experience in developing & deploying predictive machine learning models in industrial systems.

CourseRapidMiner for Machine Learning and Predictive Analytics Training Course

Target Group
Expert

Level
Foundations

Learn More
Efficient database management
Expertise in SQL databases for efficient data storage & retrieval.

CourseDatabases and SQL for Data Science with Python

Target Group
Junior (Fresh Employee)

Level
Foundations

Learn More
Big data processing
Familiarity with big data frameworks such as Hadoop & Spark for managing large datasets.

CourseIntroduction to Big Data with Spark and Hadoop

Target Group
Senior Employee

Level
Foundations

Learn More