Finalize a Data Science Project (Coursera)

Offered by CertNexus,
Finalize a Data Science Project (Coursera)

This course is designed for business professionals that want to learn how to gather results from previous stages of the data science project and present them to stakeholders. Learners will communicate the results of a model to stakeholders, be shown how to build a basic web app to demonstrate machine learning models and implement and test pipelines that automate the model training, tuning and deployment processes.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

The typical student in this course will have completed previous courses in the CDSP professional certificate program, and have several years of experience with computing technology, including some aptitude in computer programming.
Course 5 of 5 in the CertNexus Certified Data Science Practitioner Professional Certificate.
What You Will Learn

  • Communicate results of a model via web apps, and implement an d test pipelines that automate the model training, tuning and deployment process.

Syllabus

WEEK 1
Communicate Results to Stakeholders
In the previous courses in this specialization, you put your data through the extract, transform, and load (ETL) process, conducted an analysis of the data, and developed statistical models from the data that cover the three major disciplines of machine learning: classification, regression, and clustering. But you're not done yet. Now it's time to gather your results and present them to stakeholders. After all, you undertook the data science project to achieve business goals, so you need to demonstrate that you were actually successful in doing so. In this first module, you'll report your findings to the project's stakeholders.

WEEK 2
Demonstrate Models in a Web App
One way to create a robust and interesting presentation is to show off your results in a web app. In this module, you'll focus on some of the major technologies that go into creating a web app that you might want to use in a demonstration.

WEEK 3
Implement and Test Production Pipelines
Much of what you've done throughout the data science project can be automated in some way. The goal is to spend less time performing some of the more repetitive tasks, and more time on tasks that require your own judgment. This is where pipeline automation comes into play.

WEEK 4
Apply What You've Learned
You'll work on a project in which you'll apply your knowledge of the material in this course to practical scenarios.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Visualization for Data Journalism (Coursera) Coursera
University of Illinois at Urbana-Champaign

Visualization for Data Journalism (Coursera)

While telling stories with data has been part of the news practice since its earliest days, it is in the midst of a renaissance. Graphics desks which used to be deemed as “the art department,” a subfield outside the work of newsrooms, are becoming a core part of newsrooms’ operation. Those people (they often have various titles: data journalists, news artists, graphic reporters, developers, etc.) who design news graphics are expected to be full-fledged journalists and work closely with reporters and editors.

Oct 5th 2026
5-12 Weeks
Introducción a Data Science: Programación Estadística con R (Coursera) Coursera
Universidad Nacional Autónoma de México

Introducción a Data Science: Programación Estadística con R (Coursera)

Este curso te proporcionará las bases del lenguaje de programación estadística R, la lengua franca de la estadística, el cual te permitirá escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalación del lenguaje; también verás una introducción a los sistemas base de gráficos y al paquete para graficar ggplot2, para visualizar estos datos. Además también abordarás la utilización de uno de los IDEs más populares entre la comunidad de usuarios de R, llamado RStudio.

Sep 28th 2026
4 Weeks
Getting started with TensorFlow 2 (Coursera) Coursera
Imperial College London

Getting started with TensorFlow 2 (Coursera)

Welcome to this course on Getting started with TensorFlow 2! In this course you will learn a complete end-to-end workflow for developing deep learning models with Tensorflow, from building, training, evaluating and predicting with models using the Sequential API, validating your models and including regularisation, implementing callbacks, and saving and loading models.

Sep 28th 2026
5-12 Weeks
Data Science in Health Technology Assessment (Coursera) Coursera
Genentech

Data Science in Health Technology Assessment (Coursera)

This course explores key concepts and methods in Health Economics and Health Technology Assessment (HTA) and is intended for learners who have a foundation in data science, clinical science, regulatory and are new to this field and would like to understand basic principles used by payers for their reimbursement decisions.

Oct 12th 2026
3 Weeks
Foundations of Data Science: K-Means Clustering in Python (Coursera) Coursera
University of London,Goldsmiths, University of London

Foundations of Data Science: K-Means Clustering in Python (Coursera)

This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks.

Oct 5th 2026
5-12 Weeks
Data Science in Stratified Healthcare and Precision Medicine (Coursera) Coursera
University of Edinburgh

Data Science in Stratified Healthcare and Precision Medicine (Coursera)

An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare. In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine.

Oct 5th 2026
5-12 Weeks
Machine Learning Introduction for Everyone (Coursera) Coursera
IBM

Machine Learning Introduction for Everyone (Coursera)

This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more.

Oct 12th 2026
3 Weeks
Data Manipulation at Scale: Systems and Algorithms (Coursera) Coursera
University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales.

Sep 28th 2026
4 Weeks
Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 2 (Coursera)

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Sep 28th 2026
4 Weeks
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Oct 12th 2026
4 Weeks
Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera) Coursera
University of Minnesota

Introduction to Recommender Systems: Non-Personalized and Content-Based (Coursera)

This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations.

Sep 28th 2026
4 Weeks