Description

Duration

5 Days

30 CPD hours

This course is intended for

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. However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business.

Overview

In this course, you will learn to:
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.

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

Addressing Business Issues with Data Science

Topic A: Initiate a Data Science Project

Topic B: Formulate a Data Science Problem

Extracting, Transforming, and Loading Data

Topic A: Extract Data

Topic B: Transform Data

Topic C: Load Data

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

Designing a Machine Learning Approach

Topic A: Identify Machine Learning Concepts

Topic B: Test a Hypothesis

Developing Classification Models

Topic A: Train and Tune Classification Models

Topic B: Evaluate Classification Models

Developing Regression Models

Topic A: Train and Tune Regression Models

Topic B: Evaluate Regression Models

Developing Clustering Models

Topic A: Train and Tune Clustering Models

Topic B: Evaluate Clustering Models

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

Course Images

CertNexus Certified Data Science Practitioner (CDSP)

By Nexus Human

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