Data-Engineering-Kurse können Ihnen helfen zu lernen, wie Datenpipelines aufgebaut, Systeme integriert und Daten effizient verarbeitet werden. Sie können Fähigkeiten in ETL-Prozessen, Datenmodellierung, Orchestrierung und Umgang mit großen Datenmengen aufbauen. Viele Kurse stellen Tools und Plattformen für moderne Dateninfrastrukturen vor.

Kompetenzen, die Sie erwerben: Daten-Governance, SQL, Apache Spark, Datensicherheit, Datenverarbeitung, Apache Hadoop, Datenbanken, Big Data, Datenarchitektur, Data-Warehousing, NoSQL, Datenspeicher, Daten-Seen, Daten-Pipelines, Auszug, Relationale Datenbanken
Anfänger · Kurs · 1–4 Wochen

Mehrere Erzieher
Kompetenzen, die Sie erwerben: Apache Airflow, Data Modeling, Data Pipelines, Data Storage, Data Architecture, Requirements Analysis, Data Processing, Data Warehousing, Query Languages, Apache Hadoop, Extract, Transform, Load, Data Lakes, Amazon Web Services, File Systems, Apache Spark, Database Systems, Feature Engineering, Data Integration, AWS Kinesis, Data Management
Mittel · Berufsbezogenes Zertifikat · 3–6 Monate

IBM
Kompetenzen, die Sie erwerben: Python-Programmierung, MySQL, Apache Airflow, SQL, Linux-Befehle, Datenanalyse, Datenbankadministration, Apache Spark, Datenverarbeitung, Apache Hadoop, Daten importieren/exportieren, Generative KI, Datenbank-Design, IBM Cognos-Analytik, NoSQL, Data-Warehousing, Web Scraping, Datenspeicher, Auszug, Professionelles Netzwerken
Auf einen Abschluss hinarbeiten
Anfänger · Berufsbezogenes Zertifikat · 3–6 Monate

Kompetenzen, die Sie erwerben: Python-Programmierung, SQL, Daten-Governance, MySQL, Daten importieren/exportieren, IBM DB2, Datenbanken, Datenbank-Design, Big Data, Datenbank-Management-Systeme, Datenarchitektur, Datenumwandlung, Data-Warehousing, Gespeicherte Prozedur, Datenspeicher, Web Scraping, Daten-Pipelines, Auszug, Grundsätze der Programmierung, Relationale Datenbanken
Anfänger · Spezialisierung · 3–6 Monate

Snowflake
Kompetenzen, die Sie erwerben: Data Engineering, Data Pipelines, Database Management, Data Manipulation, Databases, Data Transformation, Data Lakes, Extract, Transform, Load, Data Warehousing, DevOps, Cloud Development, SQL, Data Integration, CI/CD, Application Development, Artificial Intelligence and Machine Learning (AI/ML), Role-Based Access Control (RBAC), Software Development Tools, Stored Procedure, Data Analysis
Anfänger · Berufsbezogenes Zertifikat · 1–3 Monate
Duke University
Kompetenzen, die Sie erwerben: Python-Programmierung, MySQL, SQL, Linux-Befehle, Pandas (Python-Paket), JSON, Microservices, Linux Verwaltung, Big Data, Shell-Skript, AWS SageMaker, Datenverarbeitung, Jupyter, Git (Versionskontrolle-System), Cloud-Technik, Linux, Web Scraping, Datenmanipulation, Versionskontrolle, Bash (Skriptsprache)
Anfänger · Spezialisierung · 3–6 Monate

Amazon Web Services
Kompetenzen, die Sie erwerben: Amazon CloudWatch, AWS Identitäts- und Zugriffsmanagement (IAM), AWS CloudFormation, Cloud-Anwendungen, Datenarchitektur, Serverloses Rechnen, Infrastruktur Architektur, CI/CD, Terraform, Daten-Infrastruktur, Amazon Webdienste, Sicherheitskontrollen, Infrastruktur als Code (IaC), Cloud-Technik
Anfänger · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: Feature Engineering, PySpark, Data Import/Export, Big Data, Apache Spark, Dashboard, Cloud Services, Apache Hadoop, Applied Machine Learning, Application Programming Interface (API), Apache Hive, Jupyter, Data Storage Technologies, Data Storage, Data Architecture, Artificial Intelligence and Machine Learning (AI/ML), Serverless Computing, Ad Hoc Analysis, Data Wrangling, Scalability
Mittel · Spezialisierung · 3–6 Monate

DeepLearning.AI
Kompetenzen, die Sie erwerben: Datenverarbeitung, Skalierbarkeit, Analyse der Anforderungen, Systemanforderungen, Sicherheitskontrollen, Data-Warehousing, Datenarchitektur, Datenumwandlung, Leistungsoptimierung, Cloud Computing, Amazon Webdienste, Daten-Pipelines, Auszug
Mittel · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: Real Time Data, Dataflow, Google Cloud Platform, Feature Engineering, PySpark, Data Pipelines, Cloud Storage, Data Import/Export, Big Data, Apache Spark, Data Maintenance, Data Lakes, Apache Hadoop, Dashboard, Tensorflow, Cloud Services, Data Infrastructure, Data Warehousing, Data Migration, Apache Airflow
Mittel · Berufsbezogenes Zertifikat · 3–6 Monate

Kompetenzen, die Sie erwerben: Python-Programmierung, SQL, Datenverarbeitung, Schnittstelle zur Anwendungsprogrammierung (API), Code-Überprüfung, Restful API, Datenbanken, Datenmanipulation, Datenumwandlung, Integrierte Entwicklungsumgebungen, Web Scraping, Einheitstest, Style Guides, Auszug
Mittel · Kurs · 1–4 Wochen

Kompetenzen, die Sie erwerben: MySQL, Software-Visualisierung, Linux-Befehle, Datenbankadministration, Algorithmen, Kollaborative Software, Testgetriebene Entwicklung (TDD), Linux, Datenintegrität, Django (Web-Framework), Dateiverwaltung, Computergestütztes Denken, Befehlszeilen-Schnittstelle, Data-Warehousing, Abfragesprachen, Datenbank Management, Software Versionierung, Einheitstest, Pseudocode, Datenbankarchitektur und -verwaltung
Anfänger · Berufsbezogenes Zertifikat · 3–6 Monate
Data engineering is the practice of designing, building, and maintaining the systems and architecture that enable organizations to collect, store, and analyze data effectively. It plays a crucial role in today's data-driven world, where businesses rely on data to make informed decisions, optimize operations, and enhance customer experiences. By ensuring that data is accessible, reliable, and secure, data engineers empower organizations to harness the full potential of their data assets.
In the field of data engineering, a variety of job roles are available, including Data Engineer, Data Architect, ETL Developer, and Data Warehouse Engineer. These positions often involve working with large datasets, developing data pipelines, and collaborating with data scientists and analysts to ensure that data is structured and available for analysis. With the growing demand for data professionals, opportunities in this field are expanding across industries such as finance, healthcare, technology, and retail.
To pursue a career in data engineering, you should focus on developing a range of technical skills. Key competencies include proficiency in programming languages such as Python and SQL, knowledge of data warehousing solutions, and familiarity with cloud platforms like AWS or Google Cloud. Additionally, understanding data modeling, ETL processes, and big data technologies like Hadoop and Spark can be beneficial. Soft skills such as problem-solving and effective communication are also important for collaborating with cross-functional teams.
There are several excellent online courses available for those interested in data engineering. Notable options include the DeepLearning.AI Data Engineering Professional Certificate and the IBM Data Engineering Professional Certificate. These programs provide a comprehensive curriculum that covers essential skills and tools needed in the field, making them great choices for learners at various stages of their careers.
Yes. You can start learning data engineering on Coursera for free in two ways:
If you want to keep learning, earn a certificate in data engineering, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.
To learn data engineering effectively, start by identifying your current skill level and areas for improvement. Begin with foundational courses that cover programming and database management. Gradually progress to more specialized topics such as data warehousing and cloud technologies. Engage in hands-on projects to apply what you learn, and consider joining online communities or forums to connect with other learners and professionals in the field.
Data engineering courses typically cover a range of topics, including data modeling, ETL (Extract, Transform, Load) processes, data warehousing, and big data technologies. You may also explore cloud computing platforms, data pipeline design, and data governance. Courses often include practical exercises and projects to help reinforce your understanding and application of these concepts in real-world scenarios.
For training and upskilling employees in data engineering, programs like the IBM Data Warehouse Engineer Professional Certificate and the Snowflake Data Engineering Professional Certificate are excellent choices. These courses are designed to equip professionals with the necessary skills to manage and analyze data effectively, making them suitable for organizations looking to enhance their workforce's capabilities in data engineering.