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Fortinet Network Security Expert (NSE) -programmet er et otte-niveau uddannelses- og certificeringsprogram for at undervise ingeniører i deres netværkssikkerhed for Fortinet FW-færdigheder og erfaring.

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  • +45 32 70 99 90
  • CDSP - Certified Data Science Practitioner: (Exam DSP-110)

    Duration
    5 Dage
    Delivery
    (Online Og På stedet)
    Price
    Pris på forespørgsel

    For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice.

    In this course, you will implement data science techniques in order to address business issues.

    You will:

    • Use data science principles to address business issues.
    • Apply the extract, transform, and load (ETL) process to prepare datasets.
    • Use multiple techniques to analyze data and extract valuable insights.
    • Design a machine learning approach to address business issues.
    • Train, tune, and evaluate classification models.
    • Train, tune, and evaluate regression and forecasting models.
    • Train, tune, and evaluate clustering models.
    • Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.

    Lesson 1: Addressing Business Issues with Data Science

    • Topic A: Initiate a Data Science Project
    • Topic B: Formulate a Data Science Problem

    Lesson 2: Extracting, Transforming, and Loading Data

    • Topic A: Extract Data
    • Topic B: Transform Data
    • Topic C: Load Data

    Lesson 3: Analyzing Data

    • Topic A: Examine Data
    • Topic B: Explore the Underlying Distribution of Data
    • Topic C: Use Visualizations to Analyze Data
    • Topic D: Preprocess Data

    Lesson 4: Designing a Machine Learning Approach

    • Topic A: Identify Machine Learning Concepts
    • Topic B: Test a Hypothesis

    Lesson 5: Developing Classification Models

    • Topic A: Train and Tune Classification Models
    • Topic B: Evaluate Classification Models

    Lesson 6: Developing Regression Models

    • Topic A: Train and Tune Regression Models
    • Topic B: Evaluate Regression Models

    Lesson 7: Developing Clustering Models

    • Topic A: Train and Tune Clustering Models
    • Topic B: Evaluate Clustering Models

    Lesson 8: Finalizing a Data Science Project

    • Topic A: Communicate Results to Stakeholders
    • Topic B: Demonstrate Models in a Web App
    • Topic C: Implement and Test Production Pipelines

     

    Appendix A: Mapping Course Content to CertNexus® Certified Data Science Practitioner (CDSP) (Exam DSP-110)

    This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.

    To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science. You can obtain this level of knowledge by taking the CertNexus DSBIZ™ (Exam DSZ-110) course.

    For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, it can also inform—by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice.

    In this course, you will implement data science techniques in order to address business issues.

    You will:

    • Use data science principles to address business issues.
    • Apply the extract, transform, and load (ETL) process to prepare datasets.
    • Use multiple techniques to analyze data and extract valuable insights.
    • Design a machine learning approach to address business issues.
    • Train, tune, and evaluate classification models.
    • Train, tune, and evaluate regression and forecasting models.
    • Train, tune, and evaluate clustering models.
    • Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.

    Lesson 1: Addressing Business Issues with Data Science

    • Topic A: Initiate a Data Science Project
    • Topic B: Formulate a Data Science Problem

    Lesson 2: Extracting, Transforming, and Loading Data

    • Topic A: Extract Data
    • Topic B: Transform Data
    • Topic C: Load Data

    Lesson 3: Analyzing Data

    • Topic A: Examine Data
    • Topic B: Explore the Underlying Distribution of Data
    • Topic C: Use Visualizations to Analyze Data
    • Topic D: Preprocess Data

    Lesson 4: Designing a Machine Learning Approach

    • Topic A: Identify Machine Learning Concepts
    • Topic B: Test a Hypothesis

    Lesson 5: Developing Classification Models

    • Topic A: Train and Tune Classification Models
    • Topic B: Evaluate Classification Models

    Lesson 6: Developing Regression Models

    • Topic A: Train and Tune Regression Models
    • Topic B: Evaluate Regression Models

    Lesson 7: Developing Clustering Models

    • Topic A: Train and Tune Clustering Models
    • Topic B: Evaluate Clustering Models

    Lesson 8: Finalizing a Data Science Project

    • Topic A: Communicate Results to Stakeholders
    • Topic B: Demonstrate Models in a Web App
    • Topic C: Implement and Test Production Pipelines

     

    Appendix A: Mapping Course Content to CertNexus® Certified Data Science Practitioner (CDSP) (Exam DSP-110)

    This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.

    To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science. You can obtain this level of knowledge by taking the CertNexus DSBIZ™ (Exam DSZ-110) course.

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