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| - HTML + CSS
- Programming languages (e.g., JavaScript)
- Front-end frameworks and libraries (e.g., Angular, React, Vue, etc.)
- Version control (Git + repository services like GitHub)
- RESTful services and APIs
- Testing frameworks
- Graphic design
- Web security
| - A computer science or related degree is helpful, but bootcamp grads and self-taught developers can also get hired.
- Entry-level positions are generally available.
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| - HTML + CSS
- Programming languages (e.g., JavaScript, Python, PHP, Java, SQL)
- Back-end frameworks and libraries (e.g., NodeJS, Django, Laravel)
- Relational databases (e.g., PostgreSQL, MySQL)
- NoSQL databases (e.g., MongoDB, Cassandra, Firebase)
- Version control (Git + repository services like GitHub)
- APIs
- Testing frameworks
- Web security
| - Employers often expect a computer science or related degree, but bootcamp grads and self-taught developers can also get hired.
- Entry-level positions are generally available.
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| - A combination of front-end and back-end skills and technologies
| - Employers often expect a computer science or related degree, but bootcamp grads and self-taught developers can also get hired.
- Entry-level positions are generally available.
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Machine learning engineer | - Computer science fundamentals (e.g., algorithms, data structures)
- Programming languages (e.g., SQL, Python, C++, Java, R)
- Data modeling
- ML modeling
- Mathematics, probability, and statistics
- ML algorithm optimization
- Cloud computing (e.g., AWS, Azure, Google Cloud)
- Other ML topics (e.g., deep learning, neural network architectures, natural language processing)
| - Employers usually expect a computer science or mathematics degree, and some expect an advanced degree.
- These are usually not entry-level positions. It's possible to make a career change into these roles with data engineering or software engineering experience.
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| - Programming languages (e.g., SQL, Python, Java, R)
- Relational databases (e.g., PostgreSQL, MySQL)
- NoSQL databases (e.g., MongoDB, Cassandra, Firebase)
- ETL (extract, transform, and load) systems (e.g., Xplenty, Stitch, Alooma, Talend)
- Data storage (e.g., data lakes, data warehouse)
- Automation and scripting
- Machine learning concepts and tools
- Big data tools (Hadoop, Kafka)
- Cloud computing (AWS, Azure, Google Cloud)
- Data security
| - Employers usually expect a computer science or related degree.
- For the most part, these are not entry-level positions, though you can study on your own to switch careers if you have data science or software engineering experience.
- Certifications are beneficial (e.g., IBM Certified Data Engineer, Google's Certified Professional).
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| - * Computer networking and network security (e.g., routing protocols, encryption, firewalls, virtual private networks)
- * Operating systems (e.g., Windows, MacOS, Linux)
- * Programming languages (e.g., Python, C++, Java, Ruby)
- * Computer hardware and software
- * Virus protection software
- * Data management and database platforms
- * Security protocols and standards
| - Employers usually expect a computer science or related degree.
- Entry-level positions are generally available.
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