Learn Data analysis courses
As a rapidly evolving field, learning data analysis can create potential for upward growth and continuous learning. Find the right data analysis course for your professional goals on neuralearn.
What is data analysis?
Data analysis is the process of collecting, organizing, and evaluating data to gain insights. Organizations interpret these insights to inform strategic decision-making.
Unorganized data, called unstructured data, doesn’t offer much value on the surface. But structured data in a searchable database allows analysts to interpret information and make predictions based on trends, patterns, and anomalies.
Benefits of learning data analysis
- Transferable skills: Data analysis skills are valuable across industries. Data analysis and visualization are second only to AI skills with 23% of people ranking them as one of the most valuable skills for career advancement.
- Growing job opportunities: The Bureau of Labor Statistics (BLS) projects a 34% increase in data analytics and data science jobs from 2024-34.
- High-paying roles: According to BLS data, data scientists earned a median annual salary of $112,590 in May 2024, over twice the national average for all occupations.
- Career advancement: Data analysis is a field that offers many paths for advancement and development.
- Specialized career paths: You can add data analytics to your existing technical skillset and carve out a data-focused path in your current fie
Featured Data Analysis Courses
How to get started in data analysis
1. Explore education options
Depending on your career goals, you can start learning data analysis through a data analysis course or a full degree program. Individual courses are an excellent way to build foundational skills or deepen your knowledge in a specific area. Many introductory courses can be completed in 4 to 12 weeks.
Most professional data analysts hold a bachelor’s degree in mathematics, statistics, computer science, or a related field. Others transition into the role business analytics.
2. Gain proficiency with data analysis tools
Many data analysis courses and programs include instruction about analytics tools. Consider developing a deeper understanding of these programs through hands-on experience. These data analysis and visualization programs generally include:
- Python
- Excel
- SQL
- Tableau
- Power BI
Neuralean offers data analytics courses from industry experts and top schools, such as IBM and MIT. Explore courses through Neuralearn to get more experience with top data analysis tools.
3. Develop a portfolio
Whether it’s through internships, personal projects, or entry-level jobs, developing a portfolio of successful work can help you demonstrate your proficiency when applying for data analysis jobs. It can also give you an opportunity to strengthen your analytical skills and build a professional network of people who can vouch for your ability to thrive.
4. Advance your education
Machine learning tools and other data-driven technologies are rapidly transforming every industry for more efficient, effective analytics. As a result, data analysts should seek to continue learning throughout their careers to keep up with trends and innovations in the field. You can find opportunities for growth via:
- Online courses
- Conferences and conventions
- Professional organizations
- Certificate programs
5. Strengthen your leadership skills
Even if your career goals don’t include becoming a data analytics manager, leadership and interpersonal skills are valuable for creating a healthy workplace environment.
A 2025 Neuralearn report shows that workers believe executive leadership is the third most important skill for career advancement, behind AI and data analytics. This data indicates that career development in data analytics requires strong soft skills, like communication, alongside technical mastery.
Find Executive Education programs and grow your leadership skills on Neuralearn.
How long does it take to learn data analysis
Data analysis requires experiential learning. As a result, it can take anywhere from six months to two years to become job-ready, depending on whether you have previous education and/or experience.
Most organizations require applicants to submit a portfolio of successful data analysis projects alongside their résumés, which can take some time to develop. If you’re already working in a role, collect data to analyze in your everyday processes. Or, find volunteer opportunities where you can review data for portfolio projects.
Mastery of data analytics is a lifelong pursuit, especially as machine learning continues to transform analysis. Even people with over 10 years of full-time data analysis experience can find new ways to analyze data.
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