Our Courses

DevOps, DataOps, MLOps

DevOps, DataOps, MLOps

Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications.

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  • 29 hours
  • English
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Microsoft Azure Databricks for Data Engineering

Microsoft Azure Databricks for Data Engineering

In this course, you will learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud. You will discover the capabilities of Azure Databricks and the Apache Spark notebook for processing huge files. You will come to understand the Azure Databricks platform and identify the types of tasks well-suited for Apache Spark. You will also be introduced to the architecture of an Azure Databricks Spark Cluster and Spark Jobs.

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  • 22 hours
  • English
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Data Engineering and Machine Learning using Spark

Data Engineering and Machine Learning using Spark

NOTE: This course is currently replaced with IBM Machine Learning with Apache Spark.
Further your data engineering career with this self-paced course about machine learning with Apache Spark! Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others.

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  • 8 hours
  • English
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Serverless Data Processing with Dataflow: Foundations

Serverless Data Processing with Dataflow: Foundations

This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend.

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  • 3 hours
  • English
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Cloud Virtualization, Containers and APIs

Cloud Virtualization, Containers and APIs

Welcome to the second course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn to design Cloud-native systems with the fundamental building blocks of Cloud computing. These building blocks include virtual machines and containers. You will also learn how to build effective Microservices using technologies like Flask and Kubernetes. Finally, you will analyze successful patterns in Operations including: Effective alerts, load testing and Kaizen.

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  • 14 hours
  • English
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Data Storage in Microsoft Azure

Data Storage in Microsoft Azure

Azure provides a variety of ways to store data: unstructured, archival, relational, and more. In this course, you will learn the basics of storage management in Azure, how to create a Storage Account, and how to choose the right model for the data you want to store in the cloud. This course part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services anyone interested in preparing for the Exam DP-203: Data Engineering on Microsoft Azure (beta).

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  • 16 hours
  • English
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Azure Data Lake Storage Gen2 and Data Streaming Solution

Azure Data Lake Storage Gen2 and Data Streaming Solution

In this course, you will see how Azure Data Lake Storage can make processing Big Data analytical solutions more efficient and how easy it is to set up. You will also explore how it fits into common architectures, as well as the different methods of uploading the data to the data store. You will examine the myriad of security features that will ensure your data is secure. Learn the concepts of event processing and streaming data and how this applies to Azure Stream Analytics.

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  • 9 hours
  • English
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IBM Data Engineering

IBM Data Engineering

Prepare for a career in the high-growth field of data engineering. In this program, you’ll learn in-demand skills like Python, SQL, and Databases to get job-ready in less than 5 months. Data engineering is building systems to gather data, process and organize raw data into usable information.

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  • English
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Python, Bash and SQL Essentials for Data Engineering

Python, Bash and SQL Essentials for Data Engineering

If you are interested in developing the skills needed to be a data engineer, the Python, Bash and SQL Essentials for Data Engineering Specialization is a great place to start. We live in a world that is driven by big data - from what we search online to the route we take to our favorite restaurant, and everything in between. Businesses and organizations use this data to make decisions that impact the ways in which we navigate our lives. How do engineers collect this data? How can this data be organized so that it can be appropriately analyzed?

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  • English
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Data Engineering Capstone Project

Data Engineering Capstone Project

Showcase your skills in this Data Engineering project! In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform. In this Capstone project you will complete numerous hands-on labs.

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  • 13 hours
  • English
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IBM Data Analyst

IBM Data Analyst

Prepare for a career in the high-growth field of data analytics. In this program, you’ll learn in-demand skills like Python, Excel, and SQL to get job-ready in as little as 4 months. Data analysis is the process of collecting, storing, modeling, and analyzing data that can inform executive decision-making, and the demand for skilled data analysts has never been greater. This program will teach you the foundational data skills employers are seeking for entry-level data analytics roles.

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  • English
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Data Engineering Foundations

Data Engineering Foundations

Data engineering is one of the fastest-growing tech occupations, where the demand for skilled data engineers far outweighs the supply. The goal of data engineering is to make quality data available for fact-finding and data-driven decision making. This Specialization from IBM will help anyone interested in pursuing a career in data engineering by teaching fundamental skills to get started in this field.

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  • English
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Data Science Fundamentals

Data Science Fundamentals

This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques.

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  • English
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Data Engineering Basics for Everyone

Data Engineering Basics for Everyone

Learn about data engineering concepts, ecosystem, and lifecycle. Also learn about the systems, processes, and tools you need as a Data Engineer in order to gather, transform, load, process, query, and manage data so that it can be leveraged by data consumers for operations, and decision-making.

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  • 15
  • English
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Preparing for Google Cloud Certification: Cloud Data Engineer

Preparing for Google Cloud Certification: Cloud Data Engineer

This program provides the skills you need to advance your career in data engineering and provides a pathway to earn the industry-recognized Google Cloud Professional Data Engineer certification.

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  • English
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AI Product Management

AI Product Management

Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems. This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects. This Specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems.

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  • English
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IBM Data Warehouse Engineer

IBM Data Warehouse Engineer

This Professional Certificate is intended to help you develop the job-ready skills and portfolio for an entry-level Business Intelligence (BI) or Data Warehousing Engineering position.

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  • English
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Cloud Machine Learning Engineering and MLOps

Cloud Machine Learning Engineering and MLOps

Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone.

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  • 12 hours
  • English
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Data Engineering, Big Data, and Machine Learning on GCP

Data Engineering, Big Data, and Machine Learning on GCP

87% of Google Cloud certified users feel more confident in their cloud skills.

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  • English
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Building Cloud Computing Solutions at Scale

Building Cloud Computing Solutions at Scale

With more companies leveraging software that runs on the Cloud, there is a growing need to find and hire individuals with the skills needed to build solutions on a variety of Cloud platforms. Employers agree: Cloud talent is hard to find.

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  • English
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Microsoft Azure Data Engineering Associate (DP-203)

Microsoft Azure Data Engineering Associate (DP-203)

This Professional Certificate is intended for data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services anyone interested in preparing for the Exam DP-203: Data Engineering on Microsoft Azure. This Professional Certificate will help you develop expertise in designing and implementing data solutions that use Microsoft Azure data services.

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  • English
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DataOps Methodology

DataOps Methodology

DataOps is defined by Gartner as "a collaborative data management practice focused on improving the communication, integration and automation of data flows between data managers and consumers across an organization. Much like DevOps, DataOps is not a rigid dogma, but a principles-based practice influencing how data can be provided and updated to meet the need of the organization’s data consumers.” The DataOps Methodology is designed to enable an organization to utilize a repeatable process to build and deploy analytics and data pipelines.

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  • 10 hours
  • English
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Modernizing Data Lakes and Data Warehouses with GCP en Español

Modernizing Data Lakes and Data Warehouses with GCP en Español

Los dos componentes clave de cualquier canalización de datos son los data lakes y los almacenes de datos. En este curso, se destacan los casos de uso de cada tipo de almacenamiento y se analizan en profundidad las soluciones de data lakes y almacenes disponibles en Google Cloud con detalles técnicos.

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  • Spanish
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Python for Data Science, AI & Development

Python for Data Science, AI & Development

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types.

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  • 27 hours
  • English
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Data Engineering Capstone Project

Data Engineering Capstone Project

This Capstone Project is designed for you to apply and demonstrate your Data Engineering skills and knowledge in SQL, NoSQL, RDBMS, Bash, Python, ETL, Data Warehousing, BI tools and Big Data.

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  • English
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