If you are fascinated by building tools to create beautiful products and have the mindset to check the performance of these products, then data engineering courses are for you. This interest can be further polished to shine through methods in data engineering, which enable you to contribute much to the society of data science through the development of super-awesome tools in the domain. The career as a data engineer is rated as a rapidly growing one, and there can be a whole lot of challenges in the way, making it even more fantabulous. All the upliftment in the profession depends on how much you enjoy coming out solving problems. Sweep down the list of data engineering courses enlisted, and move forward with an appropriate selection.
1. Professional Certificate in Data Engineering by Udemy
Data engineering is similar to software engineering in different ways. The data engineers are to set off with a task with a string goal and are asked to put the functional systems all together in order to reach the goal. Data engineering has even got into the stream of independent vehicle design. The course enables the learner to have a base on the pre-processing of data, in turn turning the data into a condition easier for the machines to grasp. Specific languages are also included in the study, such as java programming and python programming. Along with these, linear regression, Multivariate Linear Regression, Logistic regression, Naive Bayes Classifier, Trees, Support Vector Machines, and Random Forest are made to be done under supervision. Progressive support is provided for data mining, machine learning, developing an Artificial Neural Network in Python, and a solid understanding of Deep Convolutional Generative Adversarial Networks (DCGAN).
2. Post Graduate Program in Data Engineering by Simplilearn
The course is done in association with Purdue University along with the support from IBM and provides the correct exposure for professional development. With the united collaboration with AWS and Azure certifications, the course helps in mastering all the significant data engineering techniques. The system serves best for professionals in the field and includes topics such as the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. Live sessions are conducted along with query sessions too to get an opportunity to interact with industry experts. The providers also help in finding the best placement opportunities too.
3. Nanodegree Program by Udacity
The course enables me to lay the foundation leading to the development of a data engineer. Data engineering is the novel world of big data. The program ensures the building of production-ready data infrastructure, which is considered an excellent skill for advancing a career in data. The abilities acquired would be learning to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. The conclusion of the program helps in joining all the skills newly obtained by completing a capstone project. An intermediate level of understating of Python and SQL is recommended for the easy grasping of the subject.
4. Professional Certificate in Data Engineering by MIT xPRO
The 6-month course extends the required revolutionary skills to take the career in data engineering forward. It is an online program and requires only 15-20 hours every week. Data engineers are in the highest demand in the market as data is becoming more and more critical to business. They are capable of constructing infrastructure that is needed to put data to work. Along with all these, the MIT xPRO Professional Certificate in Data Engineering would only boost the level of the learner in the demanding job arena. The course is much suitable for STEM graduates, post-graduates, and interns who are planning to start off their career in the highly developing area with massive exposure to data engineering. It is also appropriate for software engineers and technology professionals who have decided to train themselves in the recent data engineering tools and methods; and those who are aiming to alter the profession to data engineering from IT, analytics, finance, project management, supply chain, or any other technology sector. The learner can be sure of the coding in Python, use of SQL for creating databases, squabbling and analyzing pieces of data using databases in Python, knowing about the working f networks, such as IPs, security, and servers. They also learn to manage extensive data warehousing and workflow management platforms; utilize the data engineering platforms and tools for managing data, and find out ways to discover more about artificial intelligence and machine learning concepts such as reinforcement learning and deep neural networks. The highlights of the course are; a certificate from MIT xPRO to be familiar with the skills and accomplishment, learning experiences and coding demos from renowned MIT faculty, managing of market-ready data engineering skills in a high-growth market, creating a GitHub assortment of projects that can be shared with prospective employers.
5. Data Science by UC Berkeley
The data science course is an added advantage to the career tool kit if the focus is on data engineering. It is an online course requiring only 6-8 hours weekly and can be completed within 10 weeks. The system is slightly varied from the regular data science courses, as it stresses the basics of statistics and analytics to construct groundwork in data science. There will be an acquaintance being developed with the tools of analytics, exploring the business applications of data concepts and developing the language and skills for effective working with the data team. The course completion ensures the learner to be ready to ask the right questions, create a data-driven mindset, twist data into business insights, and identifying the appropriate ways to answer the queries. Communication and interpretation of data effectively, mastering the presentation of data and conversing with data scientists along with the development of a culture of using and processing data and technology efficiently to take the data into a level of strategically driven, and execution stage coming up with excellent and correct decisions. The course is apt for mid-level managers who are preparing to upgrade to contribute to the higher impact of the organization and also for the executives who would like to start off a career in the fast-developing sector. Product managers, project managers, directors, CEOs, CTOs, CIOs, vice presidents, presidents, founders, and general managers involved in building systematic data-driven decisions in order to reinforce the application of data science in their organizations can also go for it.
6. Data Engineering Foundations Specialization by Coursera
The course offers a basic understanding and a strong base to develop into a data engineering career. The learner can be assured of earning appropriate experience in Python, SQL, and Relational Databases and become an expert in the rudiments of Data Engineering. Data engineering is a highly demanding technological field where the demand for skilled data engineers extremely overshadows the supply. Their target is to create quality data presented for finding facts and data-driven decision-making. The specialization course helps the enthusiast to follow a career in data engineering by receiving the fundamental skills to get on track on the ground. There is no strict requirement of data engineering experience to be successful in this specialization. The program mainly consists of 5 self-paced courses made available online including the skills mandatory for data engineering such as; data engineering ecosystem and lifecycle, Python, SQL, and Relational Databases. The classes are provided through appealing videos and hands-on practice using fundamental tools and real-world databases. The skills obtained can be made use indirectly to a data career, leading to the development of the base in a data engineering career. The specialization ensures the practical knowledge and experience to look deeply into data engineering and to work more on advanced data engineering projects. The projects vary from working with data in multiple formats to converting and loading the data into a single source to analyzing socio-economic data with SQL and working with advanced SQL techniques. There occurs a possibility to win a chance to work hands-on with multiple real-world databases and tools including MySQL, PostgresSQL, IBM Db2, PhpMyAdmin, pgAdmin, IBM Cloud, Python, Jupyter notebooks, Watson Studio, and much more.
7. Data Science Foundations: Data Engineering by In Learning
The confident ability to deal with big data cannot be taken up quickly. The course helps to master the essential skills required to incorporate data to work in taking care of a particular business. The topics included are the basics of data engineering, system design, analytics, and business intelligence. The tutor is an expert in data science and explains the ways to collect and organize data in order to deliver results that the organization can control. The class starts off by exploring the modern data ecosystem and its relation to managing an intelligent and efficient data hub. The course then advances to the performance of the primary errands involved in managing, loading, extracting, and transforming data. The other significant areas such as staging, profiling, cleansing, and migrating data are coming along. Specific actionable recommendations applicable to data experts throughout an organization, and those concerning analysts, engineers, scientists, and modelers are also incorporated in the course.
8. Data Engineering Basics For Everyone by EdX
The course takes the learner through the basic concepts, ecosystem, and the lifecycle of the data engineering field. The required systems, processes, and methods satisfactory for a data engineer to gather transform, load, process, question, and manage data in order to force the data consumers for operations and decision making are also incorporated in the study process. The Data Engineering Ecosystem consists of different mechanisms; data, data repositories, data integration platforms, data pipelines, different types of languages, and BI and Reporting tools. All the topics are considered in detail with every single point to be noted for the learner. The varied chances of professional excellence as a data engineer are discussed along with the core topics. Several experienced data professionals converse with the learners about the realistic and everyday aspects of being a data engineer and the desired skills and qualities that a data engineer should possess in order to be on the track and be hired by employers.
9. Microsoft Azure Data Engineering by Empire Data Systems
The Azure data engineering course is aimed at IT professionals and requires about 40 hours to get completed. They become experts in the subject, by integrating, transforming, and consolidating data from different ordered and formless data systems into structures suitable for building analytics solutions. The essential topics under scrutiny are Azure Synapse Analytics, Apache Spark, Azure Data bricks, Azure Data Factory, and Stream Analytics. The course enables the learner to be ready to aid stakeholders understand the data all the way through examination, construction, and preserving secure and submissive data processing pipelines with the use of different Azure tools and techniques. An Azure data engineer also makes sure that the data pipelines and data stores are high-performing, competent, well-thought-out, and dependable, even when working on a precise set of business requirements and limitations. The engineer will be able to deal with unforeseen issues promptly and reducing data loss. They also become competent to propose, execute, observe, and optimize data platforms in order to meet the data pipeline requests.
10. Modern Enterprise Data Engineering by Pluralsight
This is an intermediate-level course involving the how and why of the implementation of the essential ingredients which helps a business to achieve the logical swiftness to produce a spirited improvement. The course providers have a long-distance vision where data customers enthusiastically have the admittance to high-quality, cross-silo, unified enterprise data for all of their core logical entities. Data Operations is a method consisting of people, processes, tools, and services for enterprises to quickly, repetitively, and dependably convey production-ready data from the enormous arrangement of venture data sources.