CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org
Accreditedcertificate
Your data analyst career begins
Data analysts are the navigators of modern business—turning streams of data into clear direction and competitive advantage. Their insights drive smarter strategies, sharper decisions, and faster growth, making analytics one of today’s most impactful careers.
With every company relying on data, analytics is a future-proof path with opportunities across tech, finance, healthcare, and beyond.
With our data analyst courses, you’ll master the right data analyst skills—Excel, SQL, Python, visualization, and BI tools—through real-world projects.
Our training follows a proven data analyst roadmap, designed to take you from beginner to job-ready while learning at your own pace.
Curriculum
Projects
Certificates
Student outcomes
Careers
More career paths
Overview
For many aspiring data analysts, the real challenge isn’t learning data—it’s figuring out where to start.
Our structured data analyst roadmap shows you every next step—while giving you ways to test your skills and apply them in practice—so you build a practical data analyst career path that’s truly future-proof.
Along the way, you’ll build the data analyst skills employers look for, and master the essential data analyst tools, including:
Excel for data analysis and reporting
Statistics and data-driven decision-making
SQL and relational databases
Python programming
Data cleaning and preprocessing with pandas and NumPy
Data visualization with Python, R, Tableau, and Excel
In this data analyst program, you’ll go beyond concepts by working with real datasets, building visualizations, and completing industry-based projects.
Finishing with an accredited data analyst certification, you’ll be ready to compete for data analyst jobs with a strong portfolio, skills, and confidence to build a future-proof career.
Curriculum
CPE credits
ONLINE COURSE
Introduction to Data and Data Science
Discover the fundamentals of data science and understand how data analysis creates business value. Learn core concepts, tools, and roles while gaining clarity on the data analyst career path and how it connects to related fields.
Master Excel from beginner to advanced level and learn how to organize, analyze, and visualize data with confidence. This top-rated Excel course equips you with essential spreadsheet and data analysis skills used by professionals worldwide.
Build a strong foundation in statistics and learn how to apply hypothesis testing, probability, and confidence intervals in real-world scenarios. This beginner-friendly statistics course is essential for anyone starting their data analysis or data science journey.
Learn SQL from the ground up and gain the skills to manage relational databases with confidence. This beginner-friendly SQL course teaches you how to query, organize, and analyze data—essential abilities for any data analyst career path.
Start coding in Python and learn variables, data types, and functions. This beginner Python course gives aspiring data analysts essential programming skills for real-world tasks.
The Complete Data Visualization Course with Python, R, Tableau, and Excel
Learn how to create clear, professional charts and dashboards in Python, R, Tableau, and Excel. This hands-on data visualization course equips aspiring analysts with practical data analysis skills to communicate insights effectively.
Master Python’s NumPy library and learn how to clean, transform, and prepare datasets efficiently. This practical data preprocessing course equips aspiring analysts with essential skills to handle real-world problems and optimize workflows.
Master Python’s pandas library to clean, organize, and transform datasets. This pandas course teaches you to work with Series and DataFrames effectively for modern data analysis.
Discover the fundamentals of data science and understand how data analysis creates business value. Learn core concepts, tools, and roles while gaining clarity on the data analyst career path and how it connects to related fields.
Master Excel from beginner to advanced level and learn how to organize, analyze, and visualize data with confidence. This top-rated Excel course equips you with essential spreadsheet and data analysis skills used by professionals worldwide.
Build a strong foundation in statistics and learn how to apply hypothesis testing, probability, and confidence intervals in real-world scenarios. This beginner-friendly statistics course is essential for anyone starting their data analysis or data science journey.
Learn SQL from the ground up and gain the skills to manage relational databases with confidence. This beginner-friendly SQL course teaches you how to query, organize, and analyze data—essential abilities for any data analyst career path.
Start coding in Python and learn variables, data types, and functions. This beginner Python course gives aspiring data analysts essential programming skills for real-world tasks.
The Complete Data Visualization Course with Python, R, Tableau, and Excel
Learn how to create clear, professional charts and dashboards in Python, R, Tableau, and Excel. This hands-on data visualization course equips aspiring analysts with practical data analysis skills to communicate insights effectively.
Master Python’s NumPy library and learn how to clean, transform, and prepare datasets efficiently. This practical data preprocessing course equips aspiring analysts with essential skills to handle real-world problems and optimize workflows.
Master Python’s pandas library to clean, organize, and transform datasets. This pandas course teaches you to work with Series and DataFrames effectively for modern data analysis.
Measure platform feature impact on student engagement using Excel. Compare activity across two quarters to assess if gamification and content expansion drove greater engagement using statistical hypothesis testing.
Core tasks
Summarize engagement with descriptive statistics
Calculate confidence intervals for comparison
Perform hypothesis testing to assess impact
Analyze paid vs. free user behavior across time
Topics covered
Descriptive & Inferential Statistics
Engagement Metrics Analysis
Go to project
beginner
free
Calculating Free-to-Paid Conversion Rate with SQL Project
Duration: 2 hours
Case brief
Use SQL to analyze real platform data. By joining and aggregating data from multiple tables, you'll practice key SQL techniques while uncovering insights into user behavior and engagement on the 365 platform.
Core tasks
Join tables to track user registration, engagement, and purchases
Create subqueries to isolate engaged users
Write main queries to calculate conversion metrics
Interpret and analyze the results in context
Topics covered
SQL Queries
Aggregation
Conversion Rate Analysis
Go to project
beginner
free
Prime Numbers in Python Project
Duration: 1 hour
Case brief
Explore the concept of prime numbers and their practical applications in fields, including cryptography. In this project, you’ll build a Python function that checks whether a number is prime and extend it to count primes within a range. You’ll also learn how optimization plays a role in efficient number testing.
Core tasks
Write a function to check if a number is prime
Count how many primes appear in a given range
Optimize your code for better performance
Run and test your code in a Python IDE or Jupyter Notebook
Topics covered
Python Programming Basics
Number Theory
Optimization
Go to project
beginner
free
Formatting Data in Excel Professionally
Duration: 1 hour
Case brief
Format data in Excel to meet professional standards. Apply layout improvements and formatting techniques to create a clear, organized financial statement—focusing on fonts, spacing, and alignment that make your work presentation-ready. Perfect for beginners aiming to polish their Excel skills.
Core tasks
Apply consistent fonts and spacing
Format totals and subtotals for clarity
Improve the layout of a P&L statement
Create a clean, professional worksheet design
Topics covered
Excel Formatting Techniques
Financial Statement Presentation
Go to project
intermediate
Football Transfers Analysis in Excel Project
Duration: 3 hours
Case brief
Explore the economics of international football by analyzing real transfer data. Work with a two-season dataset to uncover patterns in player movements, calculate net transfer flows, and visualize financial trends across associations and countries.
Core tasks
Clean and structure transfer data by season
Analyze inbound and outbound transfers by region
Calculate total fees and net movements
Visualize key metrics using Excel charts
Topics covered
Excel Data Analysis
Sports Economics
Transfer Flows
Predictive Modeling
Go to project
intermediate
Student Streaks Analysis with SQL Project
Duration: 5 hours
Case brief
Use real platform data to identify the most consistent learners based on activity streaks. Analyze user behavior in a MySQL database and calculate each student's longest unbroken streak. It's a practical way to explore how engagement data can help uncover top users.
Core tasks
Query and explore streaks data
Calculate longest active streaks per user
Rank students by engagement duration
Identify patterns in top user behavior
Topics covered
SQL Querying
Engagement Metrics
User Analysis
Go to project
We award accredited Data Analyst certification
Receive an accredited data analyst certificate—officially recognized by leading organizations as proof that your skills align with industry standards.
Accredited by the Association of Data Scientists (ADaSci)
Accredited as an eLearning Quality Network provider (ELQN)
Quality accreditation granted from the European Agency for Higher Education & Accreditation (EAHEA)
Approved CPE* provider under NASBA—our AI bootcamp qualifies for continuing education credit
Reviewed by the Institute of Analytics (IoA)
Member of the Global Association of Online Trainers and Examiners (GAOTE)
*Note: CPE credits are reflected per course in your official transcript, in line with accreditation requirements Learn more
Where our Data Analyst career path takes you
"I come from a design background, but I wanted to combine creativity with data. 365 Data Science helped me do that. I started with data literacy, then moved into AI and the data analysis career track. The platform kept me motivated with hands-on projects and a learning experience that just made sense. Today, I work as a quality analyst in an AI company, reviewing the outputs of generative models and unsupervised learning. 365 enabled me to see the bigger picture, even beyond my direct role."
Melina A.
Before 365:
Information Design at UAM
After 365:
Data Analyst at TELUS Digital
"My background is industrial engineering. And I started my professional journey in sales. But I wanted a career that aligned with what I loved—technology and programming. 365 gave me everything: the structure, the mentorship, and the practical tools to switch. I started with math and stats, then moved on to SQL, Python, and building dashboards and apps at work. Today, I create tools that improve decision-making and manage data projects full-time—and I couldn't be happier."
Pedro A.
Before 365:
Industrial Engineer at NIBOL
After 365:
Data Manager at NIBOL
"Even after earning my master's degree, I struggled with meeting the specific requirements companies sought in data roles. Enrolling in 365 Data Science and following the career paths helped me focus on high-demand topics like probability and advanced Python. These paths streamlined my preparation for interviews and boosted my skills for the job. With constantly updated content, 365 keeps me current in the field—I'll keep using it as an essential career tool."
Vanessa V.
After 365:
Analyst at Arctic Business Consulting
"With a background in economics and over five years of experience in project management across private and international organizations—including a European Union project in Sudan—I sought new opportunities after relocating to the UAE. Transitioning into data analytics, I began my journey with the 365 Data Science platform, which provided an outstanding and well-structured learning experience. The platform's practical approach and high-quality courses helped me progress from a beginner to a proficient data analyst."
Rabab A.
Before 365:
Project Coordinator at SOFRECO
After 365:
Freelance Data Analyst
"In 2023, I decided to rewrite my story—leaving accounting to become a freelance Data and Business Analyst. At first, I was completely lost, until a friend recommended 365 Data Science. The structured learning paths, real-world projects, and clear explanations transformed my skills and confidence. Within six months, I mastered Python, built interactive dashboards, and landed five clients across four countries. 365 didn't just teach me—it reshaped my career and sparked my curiosity for AI."
Ahmed H.
Before 365:
Accountant
After 365:
International Data Analyst
"365 Data Science gave me everything I needed to succeed—clear, engaging lessons in data analysis, SQL, visualization, and machine learning. The hands-on experience boosted my confidence and helped me win multiple Datathons in Kuwait. The practical skills I developed directly led me to land a role as a data analyst. If you're serious about mastering data science and applying it to real-world challenges, 365 is your best bet."
Amro E.
Before 365:
Area Logistics Manager
After 365:
Data Analyst at GUST
I like the 365 Data Science platform, courses are well organized, practical, and detailed. I work as both a Data Analyst and an AI Project Manager simultaneously. 365 Data Science training played a crucial role in advancing my data analyst skills, as I began my self-training with 365 before even joining a Data Science Fellowship. On the job these days, juggling between AI project management and data analysis, I regularly come back to learn new areas of skills demanded on the job, such as the Power BI, Web Scraping, Power Query trainings, etc.
According to our research, many data analyst job postings list such technical degrees as computer science (28%), statistics (26%), or engineering (22%), while about 20% don’t specify a degree at all. More importantly, employers prioritize proof of ability—hands-on projects, a strong portfolio, and a recognized data analytics certification. That’s why many aspiring professionals choose data analyst courses online or enroll in structured data analyst training programs to build credibility and demonstrate their skills.
Breaking into data analytics isn’t about a degree—it’s about your skills, portfolio, and confidence.
Our data analyst training program gives you everything you need to become a data analyst—with interactive exercises, expert guidance, and real projects. Learn at your own pace and earn a data analyst certificate faster than a degree. Enroll to take the first step today.
Step 2
Skills
Hiring managers are clear about data analysis skills in demand. SQL tips the list, appearing in half of all job postings, followed by Python (33%), R (20%), and Excel (41%). Demand for data visualization expertise is also strong, with Tableau (28%) and Power BI (25%) leading the way. Beyond technical tools, employers frequently highlight that statistical analysis, forecasting, and problem-solving are essential capabilities.
What’s changing, however, is that companies are placing greater emphasis on adaptability—the ability to choose and apply the proper data analysis tool for the problem at hand.
It’s not about knowing every technique—what matters is applying the correctmethod at the right time.
Prove your abilities with practice: analyze real datasets, build Tableau/Power BI dashboards, and use SQL to uncover insights. Share projects publicly. Structured data analytics training with hands-on cases shows you’re job-ready. Join our data analyst training today.
Step 3
Branding
Your personal brand often determines whether you get noticed before the interview. A polished resume, a strong LinkedIn profile, and a portfolio or GitHub showcase your work. Sharing dashboards, SQL queries, or visualizations shows how you turn data into impact. Employers also look for credibility—data analyst certifications and data analytics certificate programs help recruiters filter applicants, and with CPE credits, they signal ongoing growth.
The real advantage lies in demonstrating flexibility in tools, reinforced by a strong portfolio and proof of continuous learning.
Feature business-impact projects: segmentation, forecasting, retention. List results and certifications on your resume. Profiles with a certified data analyst credential stand out in recruiter searches. Enroll now
But with the proper foundation—training, guidance, and credibility—you can break in and stand out, even as a beginner.
The proper support makes all the difference. Career mentors and a community of peers keep you accountable, motivated, and moving forward—so when it’s time to apply, you’re ready and confident. With guidance from industry experts, you’ll never feel alone. Follow the data analyst career path.
Is the data analyst career the right move for you? Careers in data analytics are some of the most versatile in tech—opening doors to roles like business intelligence analyst, data scientist, or data engineer.
Our free career quiz reveals where you’re most likely to thrive. In under 5 minutes, you’ll discover the perfect data analyst job that matches your skills, interests, and goals.
Yes?pursuing a data analyst career path is one of the most future-proof moves you can make. Data is at the center of decision-making in every industry?from healthcare and finance to retail and technology. Analysts enjoy substantial salaries, diverse career opportunities, and the chance to work on problems that truly impact business strategy. It?s a career that combines technical skills with creativity and problem-solving, making it both stable and rewarding in the long term.
Is 40 too old to become a data analyst?
No, 40 years old is not too old to become a data analyst. In fact, many people pivot into analytics mid-career, often coming from business, finance, or IT. What really matters isn?t age but showing you can do the work?building a strong portfolio, sharpening communication, and demonstrating tools like SQL, Excel, Tableau, and Python. With flexible data analyst courses and structured data analysis training, you can learn at your own pace and prove your expertise. Employers value diverse backgrounds and real-world perspectives, so your experience can be a strength, not a setback.
Will AI replace data analysts?
AI will not replace data analysts—it will change how they work. Automation tools can handle repetitive tasks, but companies still need analysts to interpret findings, connect insights to business goals, and communicate results clearly. According to Alteryx’s 2025 report (as cited in 365 Data Science’s Data Analyst Job Outlook 2025), 70% of analysts say AI makes their work more effective, and 87% feel more strategically valuable than ever before. To stay ahead, analysts should master essential data analyst tools and then expand into AI. Earning recognized data analytics certifications and continuing with focused data analyst training shows employers you’re serious about adapting to new technologies. Analysts who embrace these advances position themselves not just for today’s roles but for long-term career growth in data analytics.
What is the career path of a data analyst?
The career path of a data analyst usually begins with mastering essential data analysis tools like SQL, Excel, Tableau, and Python. Early roles focus on reporting and visualization, while mid-level positions involve strategy, forecasting, and more complex analytics. Over time, analysts can specialize in areas like marketing, risk, or financial analytics. By taking advanced data analytics courses and building a portfolio of projects, you can move into senior roles and even pivot to data science or leadership positions.
How to become a data analyst career path?
To follow the data analyst career path, start by building a strong foundation in statistics, SQL, and data visualization. Many learners choose structured data analysis courses or data analytics programs that provide hands-on projects. Sharing your work publicly helps prove your skills to employers. A recognized data analyst certificate or data analytics program also signals credibility and gives you an edge in the competitive job market.
How long does it take to become a data analyst?
The time it takes depends on your background and learning path. Traditional degrees can take 2 to 4 years, but focused data analytics courses online or bootcamp-style training can get you job-ready in 6 to 12 months?even without prior experience. Many learners start building projects while studying, which speeds up the transition. For those seeking extra credibility, completing a data analyst certification program can validate your abilities and make your path into the field more straightforward.
What jobs can you get with data analytics?
Completing data analytics courses can prepare you for a wide range of roles. The most common are data analyst, business intelligence analyst, operations analyst, and marketing analyst. With more experience, you can move into a senior analyst, analytics manager, or even a data scientist position. Strong data analyst skills are also valuable across industries like healthcare, finance, retail, and technology, making this a versatile and high-demand career path.
What is a data analyst?
A data analyst is an impactful and in-demand professional. They collect, organize, and interpret data to uncover patterns and trends that guide smarter decisions. Using tools like SQL, Excel, Tableau, and Power BI, they clean messy datasets, run queries, and create visualizations that make complex information easy to understand. What makes the role so impactful is its focus on turning raw numbers into meaningful stories?whether that?s helping a hospital improve patient care, a retailer forecast demand, or a tech company optimize user experience. Data analysts are the translators between data and decision-makers. With the proper data analyst training, you can step into that role?bridging the gap between data and action, and shaping outcomes across industries.
Which course is best for a data analyst?
An intense data analyst course teaches both theory and practice while helping you create a portfolio that showcases your work. Look for data analyst courses or data analytics programs that teach SQL, Excel, and data visualization with Tableau or Power BI. Ideally, the program should include real-world projects so you can demonstrate your skills to employers. Our Data Analyst Career Track brings everything together?projects, tools, and a recognized data analytics certification?in a beginner-friendly program built for professionals with little to no prior experience.
What course do I need to be a data analyst?
To become a data analyst, you need a data analysis course that covers SQL for querying databases, Excel for data manipulation, and Tableau or Power BI for visualization. Many professionals start with a flexible data analyst course online or enroll in a complete data analytics program that ends with a certification. For instance, the 365 Data Analyst Career Track combines theory and practice in one roadmap?starting with Intro to Data and Statistics, then moving through Excel, SQL, Python, and visualization. With advanced topics and interview prep included, it prepares you for diverse data analyst jobs in fields like business intelligence, operations, marketing, and finance.
What is the career path for a data analyst?
The typical data analyst career path starts with an entry-level role where you clean, analyze, and visualize data. With experience, you can move into senior analyst or business intelligence positions, and later into roles like analytics manager or consultant. Some analysts eventually transition into data scientist or data engineer roles by building advanced technical skills. Because data analyst courses give you a foundation in SQL, statistics, and visualization, they also open doors to careers in business intelligence, product analytics, risk analysis, or even strategy consulting.
