A college degree is no longer the only way to build a successful career in Data Science.
Traditional university education models require both a significant time and financial investment, a combination that has led many adult learners to question if pursuing a traditional education is worth it.
Here’s the truth: a degree is still a great way to establish the foundation of a career.
But if a degree doesn’t fit into your lifestyle or budget (or you just don’t want to go to school for another four years), a bootcamp is a viable option.
Finding the right Data Science bootcamp isn’t always easy, but it is relatively simple once you know the factors to consider and the bootcamp elements to look for.
What are the best Data Science bootcamps?
We recommend the Pace Data Science Bootcamp for remote students and the NYC Data Science Bootcamp and Codeup’s Data Science Bootcamp for learners who prefer in-person Data Science education.
1. Pace’s Data Science Bootcamp
Location: Fully remote
Commitment: Part-time (less than 15 hours per week)
Length: 24 weeks
Pace’s Data Science Bootcamp equips you with the knowledge, tools and training you need to achieve your career goals. Through this bootcamp, you’ll learn foundational Data Science concepts and strategies, learn how to analyze and organize data and better understand how to navigate the w
Data science is a field where data scientists, and other data professionals, analyze trends in data sets to give companies operations about their performance. The current demand for data transparency in the business world creates more opportunities than ever for data scientists to gather, analyze and process data in new ways.
What data science trends will define 2023?
Data science isn’t just for data scientists. 60% of the world’s companies currently use data and analytics to improve operations, a figure destined to grow in the next year. Trends in artificial intelligence, data democratization, data-as-a-service, data governance and augmented analytics could define the direction of the data science world in 2023.
1. Artificial intelligence
Artificial intelligence (AI) might conjure images of JARVIS from the Iron Man movies for some; others might picture a never-ending row of computers with complicated switches and flashing lights. In reality, AI uses an intelligent algorithm to process data automatically and utilize it for specific purposes, which means many data practices, like gathering, can be completed by computer.
Here are some examples of the ways AI can help a business:
- Optimize customer service — Many online businesses use chatbots to make customer communication more convenient, even when a live customer service agent is available to speak with a particular customer.
- Elevate productivity — Not everyone has the luxury
So, you’re interested in becoming a data specialist. Maybe it’s time for a career change? Perhaps you’ve discovered you have a talent for data organization. Whatever the reason, there’s no better time to enter the world of data analysis.
Here are the 3 steps between you and a data specialist career:
- Complete your education in data analysis.
- Develop your data analysis style through work experience.
- Continually improve your data skills.
Data specialist careers are full of potential, rich in opportunities for growth and flexibility.
Unlike more rigid career paths, data analysis has a career for virtually everyone, no matter your job goals. Here’s how to get started, in four easy steps.
What is the career path of a data specialist?
Aspiring data specialists should sign up for formal education, develop their data analysis style and pursue continuing education as data analysis trends change and evolve.
As an essential part of any organization, data specialists help businesses:
- Apply data science and data management best practices
- Use data to make sound strategic decisions
- Organize data into usable formats for all employees
- Write algorithm scripts using Python and other programming languages
Not every data specialist follows the same career path, but most follow similar steps.
First comes the education — aspiring data specialists will need education in statistics, problem solving, data visualization and other skills. There are a
One of the most promising careers within the data science world is that of data architect.
Data architects harness the power of data to make informed, accurate decisions that help them find long-lasting solutions to a wide variety of business challenges and problems. They can work in many different industries, including (but not limited to) healthcare, finance, entertainment and government.
What is a data architect?
Data architects are information technology (IT) specialists who define policies, procedures, models and systems for collecting, organizing, analyzing and storing company information.
Their exact duties and responsibilities will vary per position and per company, but there are some day-to-day responsibilities you can expect in just about every data architect’s role.
Some of these duties include:
- Creating and optimizing systems to ensure data accuracy
- Implementing data management procedures
Data science is one of the fastest growing fields in the world today — named the sexiest job of the 21st century by Harvard Business Review.
This rapid industry expansion has resulted in a massive demand for data science professionals, including data scientists. You’re only five steps from becoming a data scientist and earning an estimated $145,000 per year.
What is a data scientist?
A data scientist is someone who specializes in analyzing and interpreting different kinds of data.
They need a strong background in subjects like mathematics, statistics and computer science. They typically have a curiosity that helps them identify the most effective solutions for different complex problems, and they also possess the technical skills necessary to solve data-related problems.
There are many different careers within the data science field, each with varying res
One of the biggest differences between successful and unsuccessful companies is how well they use data. There has been a massive shift in recent decades towards analytics and data-driven solutions, which has made data science one of the largest “make or break” factors in the success or failure of modern-day organizations.
As a result, the data science industry is booming — offering thousands of new careers each year for analysts looking for positions mining, analyzing and identifying trends in corporate data sets. Positions for data scientists alone are expected to grow 36% through 2031, creating an estimated 13,500 new job openings each year.
Careers in data science: what to know
Not everyone understands or appreciates how genuinely fun, interesting and rewarding data science careers can be. Data science is an ever-evolving field and constantly expanding industry, one that has become essential for organizations who want to become and remain successful.
Nowadays, all businesses — big or small, and in all industries — require at least one person (if not a whole team of people) who can deconstruct, comprehend, organize and use data. Wit
With each new technological advancement, the data science industry grows a little wider.
Data science is one of the most rapidly-growing fields to date, and the number of in-demand career paths only continues to rise with each passing year. It is an essential component for accelerating the growth, transformation and profit of a company in a cost- and time-efficient way.
The most successful data professionals understand the importance of having a full understanding of the evolving data science world, alongside a skill set that complements the entire data science lifecycle. With well-rounded knowledge of how to capture, maintain, process, analyze and communicate data, data scientists