What to Learn After Data Science

Data science sits atop many lists as one of the most complex, wide-ranging fields in today’s market. While some data science pros specialize in analytics, others need the multidisciplinary expertise required for advanced roles in everything from SQL databases to programming languages like Python and R.

If you already know how to use data science, you might consider a deeper dive into areas like artificial intelligence (AI), machine learning, and data visualization tools like Tableau.

We’ll cover AI, ML, and data visualization here to help you better understand what skills you want to tackle next.

What is Data Science?

Data science is a broad field that encompasses the disciplines of mathematics, computer programming, and artificial intelligence (AI). Data professionals such as Data Scientists and Data Analysts use advanced techniques like machine learning algorithms to find patterns in a vast amount of information. This process can provide actionable insights to stakeholders, from Product Managers to C-suite executives.

Today nearly every sector requires data science expertise, whether public or private. Among the top sectors where data science is critical are health and wellness, retail, web and application development, banking and finance, and governmental agencies. The field continues to project dramatic growth over the next decade; Glassdoor even listed Data Scientist as number three in its 50 Best Jobs in America in 2022.

Read more about what Data Science is and why you should learn it. 

What Can You Do with Data Science?

Data science has so many applications in different industries that a comprehensive review could fill a book. Professionals as diverse as Business Analysts, Machine Learning Engineers, and Enterprise Architects use data science in their day-to-day activities.

Top sectors for data science include banking and finance, marketing and advertising, and healthcare:

• Banking, Financial Services & Insurance (BFSI) - Business Analysts and Data Scientists use data for everything from fraud detection to customized financial advice. Machine learning algorithms can assist with risk analytics, stock trading, and other tasks.

• Marketing & Advertising - Data Analysts and Marketing Analysts use data science in advertising to create targeted ad copy, recommend products and services, and leverage social media platforms. Programming languages like Python and R, often key to data science positions, help experts analyze data and make recommendations.

• In healthcare, Data Scientists create algorithms to create care plans and improve patient services. Using data analysis in medical imaging can help care providers with diagnoses and treatment decisions.

Data science has proven crucial to many other sectors, from retail and manufacturing to the public sector. If you want to combine challenging work with job security, start with data science.

Artificial Intelligence / Machine Learning

Machine learning is a subset of artificial intelligence, but the two are inextricably linked in the minds of many data science students. Top positions that typically require machine learning skills include:

• Algorithm Engineer
• Business Intelligence (BI) Developer
• Computer Network Architect
• Data Engineer
• Data Scientist
• Machine Learning Engineer
• Software Developer
• Software Engineer
• Statistician

For many data science and data analysis students, the best way to learn solid overall skills is through a comprehensive bootcamp or certificate program. Noble Desktop offers several of these, some of which cover artificial intelligence/machine learning.

Noble’s Data Science Certificate and Data Analytics Certificate both include a Python Machine Learning Bootcamp. You can also take this bootcamp through the Python Data Science and Machine Learning Bootcamp. Tools covered include the Scikit-learn, NumPy, and Pandas libraries.

Once you’ve secured an entry-level data science or Python engineering position, consider expanding your AI knowledge, especially in the area of machine learning.

Data Visualization

Fields in data science and data analytics often require the use of data visualization tools like Tableau, Power BI, or Sisense. You can expand your data visualization expertise on the job, but going into an entry-level position with the skill set may be downright necessary. Different data visualization tools require different skill sets, and your data science or analysis education will require some or perhaps all of them. Math skills, the ability to analyze the clarity of a chart or graph, and even pricing can impact the effectiveness of your data visualizations.

Several of Noble Desktop’s programs offer data visualization training. In addition to a separate Tableau Bootcamp, you can save by taking this as part of their Data Analytics Certificate program. You can also take their Power BI Bootcamp at no additional charge if you complete the Data Analytics Certificate.

Field-Specific Expertise

Data science and analytics can apply to so many fields that it’s impossible to detail what level of experience you might need in a particular sector to get a data-centered role. One thing is sure: expertise, or at least experience, in a given field always benefits job applicants. Top fields requiring data science and analytics knowledge today include:

• Banking, Financial Services & Insurance (BFSI)
• Digital Marketing and Advertising
• Healthcare
• Retail
• Telecommunications

If you already have a role in one of these sectors and want to transition to data science or analytics, your current knowledge and skill set can provide numerous benefits. Companies need Data Scientists and Data Analysts, but those with knowledge of the specific field will always be at the head of the pack.

Learn Data Science with Hands-on Training at Noble Desktop

Because data science is a broad field, targeted training can prepare you for a data-centered position or even help you choose a specific role. You might think you’ll need a four-year data science degree, but this isn’t necessarily so. The bootcamp or certificate educational model has become increasingly popular for data professionals, thanks to features like small class sizes, hands-on training from industry experts, and individual mentoring. Noble Desktop offers a wide range of data science programs to help get you started.

• Data Science Certificate - The comprehensive Data Science Certificate provides all the skills required for entry-level data science, data analytics, or software engineering roles. Students learn how to write complex queries and build machine learning models while preparing a portfolio on a real-world basis. Skills covered include Python, SQL, NumPy, Pandas, and Jupyter Notebook, to name a few.

• Data Analytics Certificate - The comprehensive Data Analytics Certificate program offers the perfect training ground for Data Analysts, Business Intelligence Analysts, and Marketing Analysts. With a heavy emphasis on Tableau data visualization software, you’ll learn skills like Python programming, SQL, and machine learning, among others. Registrants of the Data Analytics Certificate or Data Science Certificate can also attend Noble’s Power BI Bootcamp at no additional charge.

• Python for Data Science Bootcamp - The Python for Data Science Bootcamp covers everything from programming fundamentals to data visualization. Students can save by taking this course as part of Noble’s Data Science Certificate, Data Analytics Certificate, or FinTech Bootcamp.

Check out all the Noble data science classes and bootcamps for additional options, like the Python Data Science & Machine Learning Bootcamp, Python for Data Science Bootcamp, or Python Machine Learning Bootcamp.

Key Insights

• Data science and data analytics require expertise in multiple tools, including:
• Programming languages like Python and R
• Artificial intelligence, including machine learning
• SQL databases
• Data visualization tools like Tableau and Power BI
• Top sectors in urgent need of data science professionals include:
• Banking, Financial Services & Insurance (BFSI)
• Health and wellness
• Government
• Retail
• Web and app development
• Top positions in data science and analytics include:
• Algorithm Engineers
• Computer Network Architects
• Data Analysts
• Data Scientists
• Enterprise Architects
• Machine Learning Engineers
• Marketing Analysts
• Software Engineers
• Web and App Developers
• You can get in-depth Python, Power BI, and Tableau training through an in-person or live online data science bootcamp or certificate from Noble Desktop.