Kompetenzen, die Sie erwerben: Databases, Information Technology, NoSQL, Database Application, Computer Architecture, Computer Programming, Data Analysis, Data Management, Data Visualization, Distributed Computing Architecture, Plot (Graphics), Python Programming, SQL, Statistical Programming
Intermediate · Course · 1-4 Weeks
Mixed · Course · 1-3 Months
Kompetenzen, die Sie erwerben: Computer Programming, Databases, Distributed Computing Architecture, NoSQL, Python Programming, Statistical Programming
Intermediate · Guided Project · Less Than 2 Hours
Kompetenzen, die Sie erwerben: Databases, NoSQL, Big Data, Data Architecture, Data Management, Database Theory, Data Structures, Database Administration, Database Application, Data Model, Database Design, Apache, Data Warehousing, Distributed Computing Architecture, SQL, Cloud Computing, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, IBM Cloud, Network Architecture, Statistical Programming, Theoretical Computer Science
Beginner · Course · 1-3 Months
Kompetenzen, die Sie erwerben: Big Data, Data Architecture, Apache, Data Management, Databases, NoSQL, Distributed Computing Architecture, Database Theory, Database Administration, Data Structures, Database Application, Data Model, Computer Architecture, Data Analysis, Extract, Transform, Load, Applied Machine Learning, Correlation And Dependence, Feature Engineering, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Database Design, Data Warehousing, SQL, Cloud Applications, Cloud Computing, DevOps, Kubernetes, Network Architecture, Other Programming Languages, Algorithms, Computational Thinking, Computer Networking, Computer Programming, IBM Cloud, Mathematics, Theoretical Computer Science
Beginner · Specialization · 3-6 Months
Kompetenzen, die Sie erwerben: Data Management, Big Data, Data Analysis, Exploratory Data Analysis, Probability & Statistics, Distributed Computing Architecture, Machine Learning, Business Analysis, Statistical Programming, Data Science, Graph Theory, Mathematics, Apache, Computer Architecture, Databases, Data Analysis Software, NoSQL, Data Architecture, Machine Learning Algorithms, Business, Data Model, Data Structures, Spreadsheet Software, Data Mining, Python Programming, Data Visualization, SQL, Statistical Machine Learning, Statistical Visualization, Database Application, Information Technology, Cloud Computing, Software As A Service, Applied Machine Learning, Basic Descriptive Statistics, Computer Programming, Correlation And Dependence, Database Administration, Dimensionality Reduction, Feature Engineering, General Statistics, PostgreSQL, Regression, Statistical Analysis, Algorithms, Data Warehousing, Theoretical Computer Science
Beginner · Specialization · 3-6 Months
MongoDB is one of the most popular NoSQL database platforms in use today, and it has become one of the most important database systems to learn about for software development. Unlike a relational database management system (DBMS) that rigorously structures data in rows and columns, document-oriented NoSQL databases like MongoDB store information as collections of fields or ‘objects’ within a flexible data model that can evolve to meet changing schema requirements.
The agility of MongoDB is critical in the big data era, as developers must be able to iterate constantly to manage high-volume, fast-changing data inputs. MongoDB’s system of Documents and Collections makes basic CRUD (Create, Read, Update, and Delete) operations easy, and tools like aggregation frameworks greatly simplify the creation of data pipelines and other critical pieces of infrastructure that data science applications rely upon.
Because of the industry-leading flexibility of the MongoDB platform, a background in this DBMS has become increasingly essential to pursuing a career as a data engineer, data scientist, or software developer. Building applications that effectively harness big data is exciting but challenging work, and the ability of MongoDB’s data model to evolve alongside developer needs is an ideal fit for agile software development processes that emphasize constant iteration.
MongoDB expertise can also be invaluable for a career as a database administrator (DBA). While many DBAs have traditionally worked with relational database models, the ability to ensure a MongoDB database operates efficiently and securely can be an important differentiator for hiring at many tech companies. According to the Bureau of Labor Statistics, DBAs make a median salary of $83,750 per year, and their expected job growth is faster than average due to the increasing use of data across all industries.
Absolutely. Computer science and data science courses are some of the most popular learning opportunities on the Coursera platform, and you have a range of options to learn about MongoDB. If you need to add MongoDB skills to your resume specifically, Coursera lets you learn from the source through courses offered by MongoDB itself. You can also learn by completing hands-on, step-by-step MongoDB tutorials from experienced instructors as part of the Coursera Project Network.
Alternatively, if you want to learn about MongoDB within the context of a broader education in computer science and big data, you can take individual courses or even Specializations spanning multiple courses provided by top-ranked universities from all over the world. Coursera offers terrific learning opportunities in this field from the University of California San Diego, Universidad Nacional Autónoma de México, The Hong Kong University of Science and Technology, and more - all at a lower tuition price than on-campus students.
Before starting to learn MongoDB, be sure to have an understanding of the basic concepts of databases. These include concepts like the different types of databases, the five main components of a database, and what a database management system (DBMS) is. You'll also need a grasp of basic terminologies related to databases, such as relations, tuples, attributes, degrees, text editor, execution of programs, and cardinality, among others. You'll also benefit from experience using NoSQL, since MongoDB is a NoSQL database, as well as C++, the language MongoDB is written in.
Learning MongoDB is likely right for you if you're a software professional who wants to have access to a cross-platform that provides high availability, high performance, and easy scalability. MongoDB can be used for big data, mobile and social infrastructure, user data management, content management and delivery, and as a data hub, so if this meets your needs, learning MongoDB is likely a good fit for you. Also, MongoDB has certain advantages over a relational database management system (RDBMS), including that it is document-based so it's schema-less, it has no complex joins, it's easy to scale, conversion and mapping of application objects to database objects is not needed, and it uses internal memory for storing working sets so data is accessed faster. If these sound like advantages you're looking for, learning MongoDB may be your next step.
Places that hire people with a background in MongoDB include companies and organizations that hire software developers and software engineers. You might find career opportunities working for MongoDB, Inc. itself, especially in its engineering department. And companies and government organizations that use MongoDB to manage their data may also hire people with this background. These include thousands of customers across the world, a few of which are Barclays, Verizon, Gap, Royal Bank of Scotland, SAP, SEGA, eBay, Google, and Adobe.