Introduction Data Science (EN)

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What is Introduction Data Science

Data Science, hailed as “The sexiest job of the 21st century” by the Harvard Business Review in 2012, is an extension of classic data analysis. It involves making predictions and discovering patterns from large amounts of data, providing valuable information for decision-making. In this training, you’ll learn to spot opportunities for potential Data Science projects and take the first steps towards real Data Science work. You’ll be introduced to terms such as the Data Science Cycle, Supervised Learning, Unsupervised Learning, Time Series Forecasting, Natural Language Processing, and Computer Vision. We’ll discuss different types of Data Science methodologies and models, and the importance of correct problem statement formulation and data preparation for the validity of your analysis. The training revolves around the question, “I have problem X, how do I solve this with the help of data?” Participants are challenged to apply theory to practical cases. The training is delivered by practitioners who carry out Data Science projects and are eager to share their practical knowledge.

Embarking on a journey with our Data Science training paves the way to a multitude of opportunities. Our trainers, with their extensive expertise, bring theoretical concepts to life by infusing them with practical insights and best practices from the real world. This immersive training experience is designed to arm you with the necessary skills to steer your way through the dynamic and thrilling realm of Data Science.

Who should attend Introduction Data Science

• People who want to become a Data Analyst or Data Scientist: Enhance your analytical skills and learn to make predictions and discover patterns from large amounts of data.
• Data Enthusiasts: Individuals interested in the field of Data Science.
• Business Analysts: Learn to spot opportunities for potential Data Science projects within your organization.
• IT Professionals: Gain an understanding of Data Science methodologies and models and learn how to apply them in your work.

Prerequisites

Basic skills and general knowledge of data analysis. The 'Introduction to Data Analysis' training addresses these topics and is ideally suited to follow as a training course prior to this.
During this training you need a laptop with access to internet.

Objectives

At the end of the training, you will be able to:

• Identify the steps in a typical Data Science project.
• Understand the difference between Supervised and Unsupervised learning and know when to use each.
• Identify common pitfalls in Data Science projects and learn how to avoid them.

287454

What is Introduction Data Science

Data Science, hailed as “The sexiest job of the 21st century” by the Harvard Business Review in 2012, is an extension of classic data analysis. It involves making predictions and discovering patterns from large amounts of data, providing valuable information for decision-making. In this training, you’ll learn to spot opportunities for potential Data Science projects and take the first steps towards real Data Science work. You’ll be introduced to terms such as the Data Science Cycle, Supervised Learning, Unsupervised Learning, Time Series Forecasting, Natural Language Processing, and Computer Vision. We’ll discuss different types of Data Science methodologies and models, and the importance of correct problem statement formulation and data preparation for the validity of your analysis. The training revolves around the question, “I have problem X, how do I solve this with the help of data?” Participants are challenged to apply theory to practical cases. The training is delivered by practitioners who carry out Data Science projects and are eager to share their practical knowledge.

Embarking on a journey with our Data Science training paves the way to a multitude of opportunities. Our trainers, with their extensive expertise, bring theoretical concepts to life by infusing them with practical insights and best practices from the real world. This immersive training experience is designed to arm you with the necessary skills to steer your way through the dynamic and thrilling realm of Data Science.

Who should attend Introduction Data Science

• People who want to become a Data Analyst or Data Scientist: Enhance your analytical skills and learn to make predictions and discover patterns from large amounts of data.
• Data Enthusiasts: Individuals interested in the field of Data Science.
• Business Analysts: Learn to spot opportunities for potential Data Science projects within your organization.
• IT Professionals: Gain an understanding of Data Science methodologies and models and learn how to apply them in your work.

Prerequisites

Basic skills and general knowledge of data analysis. The 'Introduction to Data Analysis' training addresses these topics and is ideally suited to follow as a training course prior to this.
During this training you need a laptop with access to internet.

Objectives

At the end of the training, you will be able to:

• Identify the steps in a typical Data Science project.
• Understand the difference between Supervised and Unsupervised learning and know when to use each.
• Identify common pitfalls in Data Science projects and learn how to avoid them.