Coursera

Extract, Transform, and Load Data (Coursera)

Offered by CertNexus,
Extract, Transform, and Load Data (Coursera)

This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL. Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination

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

In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled.
The typical student in this course will have experience working with data and aptitude with computer programming.

Course 2 of 5 in the CertNexus Certified Data Science Practitioner Professional Certificate.

Syllabus

WEEK 1
Extract Data
The first truly hands-on technical phase of the data science process is actually a combination of related tasks known as extract, transform, and load (ETL). This is where you, the data science practitioner, start to mold and shape the data so that it can be as useful as possible for the later steps in the data science process. In this course, you'll go through each ETL task in order, starting with "E" (extract).

WEEK 2
Transform Data
The next step in the ETL process is transformation. You'll spend this next module adjusting your data so that it's in a more useful state.

WEEK 3
Load Data
The last step in the ETL process is loading. In this module, you'll take the data you transformed and put it into a destination format and location, where it will be ready for you to work on as the project progresses.

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 a practical scenario.

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

Related Courses

Introdução à Ciência e Engenharia de Dados (Coursera) Coursera
FIA Business School

Introdução à Ciência e Engenharia de Dados (Coursera)

Statistics & Data Analysis

Neste curso, você aprenderá que os dados se tornaram o principal ativo de negócios nos dias de hoje. Com o aumento do Big Data e criação de novas tecnologias, as organizações em todo o mundo estão inovando e descobrindo novas formas para analisar o potencial dos dados à sua disposição, o que ajuda no crescimento, na lucratividade, no direcionamento das operações gerais e no aumento da satisfação do cliente. Mas para que tudo isso funcione corretamente e seja possível extrair todo o potencial de forma precisa e que seja viável para o negócio, criou-se a área de ciência de dados.

Jul 20th 2026
4 Weeks
Artificial Intelligence Big Data Data Mining
Details
Data Visualization with Python & R for Engineers (Coursera) Coursera
Northeastern University

Data Visualization with Python & R for Engineers (Coursera)

Statistics & Data Analysis Data Science

The primary objective of this course is to offer students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. This course covers basics of data mining and visualization, and Python. It also introduces students to static visualization charts and techniques that reveal information, patterns, interactions.

Aug 3rd 2026
4 Weeks
Python Data Mining Data Visualization
Details
Train Machine Learning Models (Coursera) Coursera
CertNexus

Train Machine Learning Models (Coursera)

Data Science

This course is designed for business professionals that wish to identify basic concepts that make up machine learning, test model hypothesis using a design of experiments and train, tune and evaluate models using algorithms that solve classification, regression and forecasting, and clustering problems. To be successful in this course a learner should have a background in computing technology, including some aptitude in computer programming.

Jul 20th 2026
5-12 Weeks
ML Machine Learning Clustering
Details
Data Warehousing and Business Intelligence (Coursera) Coursera
University of California, Irvine

Data Warehousing and Business Intelligence (Coursera)

CS: Information & Technology

This course builds on “The Nature of Data and Relational Database Design” to extend the process of capturing and manipulating data through data warehousing and data mining. Once the transactional data is processed through ETL (Extract, Transform, Load), it is then stored in a data warehouse for use in managerial decision making. Data mining is one of the key enablers in the process of converting data stored in a data warehouse into actionable insight for better and faster decision making.

Jul 27th 2026
4 Weeks
Clustering Classification Data Mining
Details
Association Rules Analysis (Coursera) Coursera
University of Colorado Boulder

Association Rules Analysis (Coursera)

Statistics & Data Analysis Data Science

The "Association Rules and Outliers Analysis" course introduces students to fundamental concepts of unsupervised learning methods, focusing on association rules and outlier detection. Participants will delve into frequent patterns and association rules, gaining insights into Apriori algorithms and constraint-based association rule mining. Additionally, students will explore outlier detection methods, with a deep understanding of contextual outliers. Through interactive tutorials and practical case studies, students will gain hands-on experience in applying association rules and outlier detection techniques to diverse datasets.

Jul 20th 2026
5-12 Weeks
Data Mining Unsupervised Learning Coursera Plus
Details
Predictive Modeling and Analytics (Coursera) Coursera
University of Colorado Boulder

Predictive Modeling and Analytics (Coursera)

Statistics & Data Analysis Data Science

Welcome to the second course in the Data Analytics for Business specialization! This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business.

Jul 20th 2026
4 Weeks
Data Analysis Analytics Data Cleaning
Details
Cluster Analysis in Data Mining (Coursera) Coursera
University of Illinois at Urbana-Champaign

Cluster Analysis in Data Mining (Coursera)

Statistics & Data Analysis Data Science

Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications.

Jul 27th 2026
4 Weeks
Algorithms Clustering Data Mining
Details