{"id":13308,"date":"2026-05-16T16:22:08","date_gmt":"2026-05-16T10:52:08","guid":{"rendered":"https:\/\/ivyproschool.com\/blog\/?p=13308"},"modified":"2026-05-16T17:52:10","modified_gmt":"2026-05-16T12:22:10","slug":"can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\/","title":{"rendered":"Can a Non-IT Person Learn Data Science? A Complete Guide for Beginners"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"13308\" class=\"elementor elementor-13308\">\n\t\t\t\t\t\t<div class=\"elementor-inner\">\n\t\t\t\t<div class=\"elementor-section-wrap\">\n\t\t\t\t\t\t\t\t\t<section class=\"has_ma_el_bg_slider elementor-section elementor-top-section elementor-element elementor-element-4b8b48c6 elementor-section-boxed elementor-section-height-default elementor-section-height-default jltma-glass-effect-no\" data-id=\"4b8b48c6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"has_ma_el_bg_slider elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-64e93585 jltma-glass-effect-no\" data-id=\"64e93585\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c97d6fc jltma-glass-effect-no elementor-widget elementor-widget-image\" data-id=\"c97d6fc\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1080\" height=\"608\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg-1080x608.jpeg\" class=\"attachment-large size-large wp-image-13326\" alt=\"Can a Non-IT Person Learn Data Science\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg-1080x608.jpeg 1080w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg-300x169.jpeg 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg-150x84.jpeg 150w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg-768x432.jpeg 768w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg-1536x864.jpeg 1536w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg.jpeg 1920w\" sizes=\"auto, (max-width: 1080px) 100vw, 1080px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7a3b584 uael-heading-align-left jltma-glass-effect-no elementor-widget elementor-widget-ma-table-of-contents\" data-id=\"7a3b584\" data-element_type=\"widget\" data-widget_type=\"ma-table-of-contents.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"jltma-toc-main-wrapper\" data-jltma-headings=\"h2\">\n\t\t\t<div class=\"jltma-toc-wrapper\">\n\t\t\t\t<div class=\"jltma-toc-header\">\n\t\t\t\t\t<span class=\"jltma-toc-heading elementor-inline-editing\" data-elementor-setting-key=\"heading_title\" data-elementor-inline-editing-toolbar=\"basic\">Table of Contents<\/span>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<div class=\"jltma-toc-toggle-content\">\n\t\t\t\t\t<div class=\"jltma-toc-content-wrapper\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<ul data-toc-headings=\"headings\" class=\"jltma-toc-list jltma-toc-list-disc\" data-jltma-scroll=\"\"><\/ul>\n\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"jltma-toc-empty-note\">\n\t\t\t\t\t<span>Add a header to begin generating the table of contents<\/span>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1c939651 jltma-glass-effect-no elementor-widget elementor-widget-text-editor\" data-id=\"1c939651\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p><span style=\"font-weight: 400;\">Many people believe that data science is only for software engineers, coders, or people from a computer science background. This is one of the biggest myths stopping talented professionals from entering the field. The truth is simple: <\/span><b>Can a non-IT person learn <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a><\/b><span style=\"font-weight: 400;\">? Yes, absolutely.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Data science is not just about writing code. It is about understanding data, asking the right questions, finding patterns, solving business problems, and communicating insights clearly. In fact, many non-IT professionals already use data in their daily work without calling it \u201cdata science.\u201d Sales teams analyze targets, finance teams study costs, HR teams review attrition, marketing teams track campaigns, and operations teams monitor performance. Data science simply gives structure, tools, and advanced techniques to do this better.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So, if you are from commerce, management, economics, statistics, engineering, HR, sales, finance, operations, or even a completely different background, this blog will help you understand how you can enter the field confidently.<\/span><\/p>\n<h2><b>What Does Data Science Actually Mean?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Before answering <\/span><b>Can a non-IT person learn <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a><\/b><span style=\"font-weight: 400;\">, it is important to understand what data science really is.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Data science is the process of collecting, cleaning, analyzing, visualizing, and interpreting data to solve problems or support decision-making. It combines different skills such as statistics, business understanding, programming, machine learning, and communication.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, a retail company may want to know why sales dropped in a particular region. A <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a> approach would include collecting sales data, comparing it across locations and time periods, finding possible reasons, visualizing the trends, and recommending business actions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Similarly, a bank may use data science to identify customers who are likely to default on loans. A hospital may use it to predict patient demand. An e-commerce company may use it to recommend products. A manufacturing company may use it to forecast defects or machine downtime.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This shows that data science is not limited to IT companies. It is used across industries and functions.<\/span><\/p>\n<h2><b>Can a Non-IT Person Learn Data Science Without Coding Experience?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">The most common fear beginners have is coding. Many people think, \u201cI am not from IT, so how will I learn <a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/python-basics\/merge-csv-files\">Python<\/a>, SQL, or <a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/machine-learning\/decision-tree-vs-random-forest\">machine learning<\/a>?\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Here is the reality: coding is a skill, not a background requirement. Nobody is born knowing Python or SQL. Even IT professionals learn them step by step.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So, <\/span><b>Can a non-IT person learn data science<\/b><span style=\"font-weight: 400;\"> without coding experience? Yes. You can start with beginner-friendly tools and gradually move toward programming.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A good learning path usually begins with Excel, statistics, and business problem-solving. Then you can learn SQL for working with databases. After that, Python becomes easier because you already understand what you want to do with data.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Python for <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a> is not the same as advanced software development. You do not need to build complex applications at the beginning. You mainly need to learn how to import data, clean it, analyze it, create charts, and build basic models.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For many learners, the fear of coding disappears once they start applying it to real examples.<\/span><\/p>\n<p><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-13334\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7-300x75.jpeg\" alt=\"\" width=\"300\" height=\"75\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7-300x75.jpeg 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7-1080x271.jpeg 1080w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7-150x38.jpeg 150w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7-768x192.jpeg 768w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7-1536x385.jpeg 1536w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/1.jpg-7.jpeg 1920w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<h2><b>Why Non-IT Professionals Can Actually Do Well in Data Science<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">A non-IT background can become a strength in data science, especially if you already understand business processes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, a finance professional understands revenue, cost, profit, margins, and risk. A marketing professional understands customer behavior, campaign performance, segmentation, and conversion. An HR professional understands hiring, attrition, employee engagement, and performance. A supply chain professional understands inventory, logistics, demand, and vendor performance.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">These domain skills are extremely valuable.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Many technical learners know how to build models but may struggle to understand the business context. On the other hand, a non-IT professional may understand the business problem better and can learn the required tools to analyze it.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This is why the answer to <\/span><b>Can a non-IT person learn data science<\/b><span style=\"font-weight: 400;\"> is not only yes, but also that they may bring a unique advantage.<\/span><\/p>\n<h2><b>Skills Required to Learn Data Science<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">To become good at <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a>, you need a combination of technical and analytical skills. You do not need to master everything on day one. You can build these skills gradually.<\/span><\/p>\n<h3><b>1. Basic Mathematics and Statistics<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Statistics is the foundation of data science. You should understand concepts like average, median, percentage, variance, correlation, probability, hypothesis testing, and distribution.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The good news is that you do not need advanced mathematics at the beginner stage. Most real business problems require practical statistical thinking rather than complicated formulas.<\/span><\/p>\n<h3><b>2. Excel and Data Handling<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Excel is a great starting point for non-IT learners. It helps you understand rows, columns, formulas, filters, pivot tables, charts, and basic analysis.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you are already comfortable with Excel, you already have a strong foundation for data science.<\/span><\/p>\n<h3><b>3. SQL<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">SQL is used to extract and work with data from databases. It is one of the most important skills for data analysts and data scientists.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">SQL is easier than most programming languages because it uses a structured query format. You can learn basic SQL queries like SELECT, WHERE, GROUP BY, JOIN, and ORDER BY within a few weeks of practice.<\/span><\/p>\n<h3><b>4. Python<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Python is widely used in <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a> because it is simple and powerful. Libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn help you clean data, analyze it, visualize it, and build machine learning models.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For beginners, the focus should be on Python for data analysis, not advanced software development.<\/span><\/p>\n<h3><b>5. Data Visualization<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">A data scientist must know how to present insights clearly. Tools like Power BI, Tableau, Excel dashboards, and <a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/python-basics\/excel-automation-openpyxl\">Python<\/a> visualization libraries are useful here.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Good visualization helps decision-makers understand what the data is saying.<\/span><\/p>\n<h3><b>6. Machine Learning<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Machine learning helps computers learn patterns from data. As a beginner, you can start with simple concepts like regression, classification, clustering, and decision trees.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">You do not need to become a machine learning researcher. You need to understand how models work, when to use them, and how to evaluate their performance.<\/span><\/p>\n<h3><b>7. Business Problem-Solving<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">This is where non-IT learners can shine. Data science is valuable only when it solves real problems. You should learn how to convert a business question into a data question.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, \u201cWhy are customers leaving?\u201d becomes a churn analysis problem. \u201cWhich product should we promote?\u201d becomes a sales and customer segmentation problem.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-13335\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8-300x75.jpeg\" alt=\"\" width=\"300\" height=\"75\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8-300x75.jpeg 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8-1080x271.jpeg 1080w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8-150x38.jpeg 150w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8-768x192.jpeg 768w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8-1536x385.jpeg 1536w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/2.jpg-8.jpeg 1920w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<p><\/p>\n<h2><b>Best Learning Path for Non-IT Learners<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">If you are wondering <\/span><b>Can a non-IT person learn <a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/career\/data-science-for-commerce-students\">data science<\/a><\/b><span style=\"font-weight: 400;\"> in a structured way, follow this practical path.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Start with Excel and basic statistics. Learn how to clean data, create pivot tables, calculate key metrics, and build simple dashboards. Then move to SQL and learn how to extract data from databases.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Once you are comfortable with SQL, start Python. Focus on Python basics first, then move to Pandas for data cleaning and analysis. After this, learn visualization using Power BI, Tableau, or Python libraries.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Then move to machine learning basics. Start with simple projects like predicting house prices, classifying customers, forecasting sales, or analyzing employee attrition.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Finally, build a project portfolio. This is extremely important for career transition. Employers want to see whether you can apply your skills to real-world problems.<\/span><\/p>\n<h2><b>Common Challenges Faced by Non-IT Learners<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Learning <a href=\"https:\/\/ivyproschool.com\/courses\/data-science-and-ml-course\">data science<\/a> as a non-IT person is possible, but it does come with challenges.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The first challenge is fear of coding. Many learners give up before they even start because Python looks unfamiliar. The solution is to learn coding through practical examples rather than theory.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The second challenge is trying to learn too much at once. <a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/career\/data-science-for-commerce-students\">Data science<\/a> has many topics, and beginners often feel overwhelmed. The solution is to follow a step-by-step roadmap.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The third challenge is lack of practice. Watching videos is not enough. You need to work on datasets, solve problems, and build projects.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The fourth challenge is not connecting <a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/career\/data-science-for-commerce-students\">data science<\/a> with business use cases. Many learners focus only on tools and forget the problem-solving part. This makes their learning incomplete.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The fifth challenge is comparison. Non-IT learners often compare themselves with coders. This is unnecessary. Your journey will be different, but it can still be successful.<\/span><\/p>\n<h2><b>How Long Does It Take for a Non-IT Person to Learn Data Science?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">The timeline depends on your background, consistency, and learning approach.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you study regularly for 8 to 10 hours per week, you can build a strong foundation in 6 to 9 months. This includes Excel, SQL, Python, statistics, visualization, and basic machine learning.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you already know Excel, business analytics, finance, or statistics, your journey may be faster. If you are completely new to data, it may take longer.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But the real answer is not just about duration. The quality of practice matters more. A learner who completes 5 strong projects in 6 months may be more job-ready than someone who watches videos for one year without applying anything.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So, when people ask <\/span><b>Can a non-IT person learn data science<\/b><span style=\"font-weight: 400;\">, the better question is: Are they willing to practice consistently?<\/span><\/p>\n<p><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-medium wp-image-13337\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5-300x75.jpeg\" alt=\"\" width=\"300\" height=\"75\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5-300x75.jpeg 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5-1080x271.jpeg 1080w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5-150x38.jpeg 150w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5-768x192.jpeg 768w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5-1536x385.jpeg 1536w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2021\/05\/3.jpg-5.jpeg 1920w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/p>\n<h2><b>Career Opportunities After Learning Data Science<\/b><\/h2>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/ivyproschool.com\/aihelpcenter\/career\/how-to-build-a-data-science-portfolio-without-experience\">Data science<\/a> opens up multiple career paths. You do not have to become a data scientist immediately. Many non-IT professionals begin with roles that match their current strengths.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Some popular roles include:<\/span><\/p>\n<table>\n<tbody>\n<tr>\n<td><b>Role<\/b><\/td>\n<td><b>Suitable For<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Data Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Beginners, Excel users, business professionals<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Business Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Management, operations, finance, sales backgrounds<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">BI Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">People interested in dashboards and reporting<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Marketing Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Marketing and digital campaign professionals<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">HR Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">HR and talent management professionals<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Financial Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Commerce, finance, accounting backgrounds<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Machine Learning Analyst<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Learners comfortable with Python and models<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Data Scientist<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Learners with stronger statistics, coding, and ML skills<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><span style=\"font-weight: 400;\">&nbsp;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This means you do not need to jump directly into the most advanced role. You can enter through analytics and gradually grow into <a href=\"https:\/\/ivyproschool.com\/blog\/how-to-become-a-data-scientist-without-a-degree-complete-career-roadmap\/\">data science<\/a>.<\/span><\/p>\n<h2><b>Which Backgrounds Are Good for Data Science?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Many non-IT backgrounds are suitable for <a href=\"https:\/\/ivyproschool.com\/blog\/how-to-become-a-data-scientist-without-a-degree-complete-career-roadmap\/\">data science<\/a>.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Commerce students can understand business numbers, accounting, finance, and reporting. MBA graduates can connect data with strategy and decision-making. Economics students often have good analytical and statistical thinking. Engineers from non-computer branches can bring logical thinking and process understanding. HR, sales, marketing, and operations professionals bring domain knowledge.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Even teachers, researchers, entrepreneurs, and consultants can learn <a href=\"https:\/\/ivyproschool.com\/blog\/how-to-become-a-data-scientist-without-a-degree-complete-career-roadmap\/\">data science<\/a> if they follow the right roadmap.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So, <\/span><b>Can a non-IT person learn data science<\/b><span style=\"font-weight: 400;\"> from any background? Yes, provided they are ready to learn the tools, practice regularly, and build projects.<\/span><\/p>\n<h2><b>How to Build a Strong Portfolio<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">A portfolio is one of the most important parts of your career transition. It shows employers that you can work with real data.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Your portfolio should include projects from different areas such as sales analysis, customer segmentation, financial analysis, HR attrition analysis, inventory analysis, social media analysis, and predictive modeling.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Each project should clearly explain the business problem, dataset used, steps followed, tools applied, insights found, and recommendations given.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Do not simply upload code. Tell a story through your project. Recruiters and hiring managers should be able to understand what problem you solved and what value your analysis created.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">A strong portfolio can help non-IT learners compete with technical candidates.<\/span><\/p>\n<h2><b>Practical Tips for Non-IT Learners<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Start small. Do not begin with advanced machine learning or deep learning. Build your foundation first.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Learn one tool at a time. For example, do not try to learn Excel, SQL, Python, Power BI, and machine learning all in the same week.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Practice on real datasets. Use business datasets whenever possible because they are easier to relate to.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Focus on problem-solving. Tools will keep changing, but analytical thinking will always remain valuable.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Build projects and publish them on LinkedIn or a portfolio website. Visibility matters.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Learn how to explain your work. A data professional must communicate insights, not just produce charts or code.<\/span><\/p>\n<h2><b>Final Answer: Can a Non-IT Person Learn Data Science?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Yes. <\/span><b>Can a non-IT person learn data science<\/b><span style=\"font-weight: 400;\">? Definitely. <a href=\"https:\/\/ivyproschool.com\/blog\/how-to-become-a-data-scientist-without-a-degree-complete-career-roadmap\/\">Data science<\/a> is not reserved for IT professionals. It is open to anyone who is curious, analytical, consistent, and willing to learn.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">You do not need to know coding before starting. You do not need a computer science degree. You do not need to be a mathematics genius. What you need is a structured roadmap, regular practice, real projects, and the ability to connect data with business problems.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In fact, non-IT professionals often bring valuable domain knowledge that can make them stronger data professionals. A finance person can become a finance analytics expert. A marketing person can become a marketing analyst. An HR person can become an HR analytics specialist. An operations professional can become a supply chain analytics expert.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The best way to start is simple: learn Excel and statistics, move to SQL, then Python, then visualization and machine learning. Build projects at every stage.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">So, the next time someone asks <\/span><b>Can a non-IT person learn data science<\/b><span style=\"font-weight: 400;\">, the answer is clear: yes, and with the right guidance, they can build a strong and rewarding career in the data field.<\/span><\/p><p><span style=\"font-weight: 400;\"><br><\/span><\/p><h2 data-section-id=\"1xvwnkw\" data-start=\"0\" data-end=\"7\">FAQs<\/h2><h3 data-section-id=\"1hkrgi9\" data-start=\"9\" data-end=\"55\">1. Can a non-IT person learn data science?<\/h3><p data-start=\"57\" data-end=\"254\">Yes, a non-IT person can learn data science with the right roadmap. You can start with Excel, basic statistics, and business analysis before moving to SQL, Python, dashboards, and machine learning.<\/p><h3 data-section-id=\"1qy2dl4\" data-start=\"256\" data-end=\"312\">2. Do I need coding knowledge to start data science?<\/h3><p data-start=\"314\" data-end=\"479\">No, you do not need coding knowledge to start. Coding can be learned step by step. Many beginners first learn Excel, SQL, and basic analytics before learning Python.<\/p><h3 data-section-id=\"1bktbvk\" data-start=\"481\" data-end=\"541\">3. Is data science difficult for non-technical students?<\/h3><p data-start=\"543\" data-end=\"772\">Data science may feel challenging in the beginning, but it becomes easier when you learn through practical examples and real projects. The key is to follow a structured learning path instead of trying to learn everything at once.<\/p><h3 data-section-id=\"42esyp\" data-start=\"774\" data-end=\"832\">4. Which background is best for learning data science?<\/h3><p data-start=\"834\" data-end=\"1064\">Students and professionals from commerce, economics, statistics, management, finance, marketing, HR, operations, and engineering backgrounds can all learn data science. A strong business understanding can actually be an advantage.<\/p><h3 data-section-id=\"fico0o\" data-start=\"1066\" data-end=\"1137\">5. How long does it take for a non-IT person to learn data science?<\/h3><p data-start=\"1139\" data-end=\"1322\">With regular practice, a non-IT learner can build a strong foundation in around 6 to 9 months. The timeline depends on your current skills, learning consistency, and project practice.<\/p><h3 data-section-id=\"nqjcqs\" data-start=\"1324\" data-end=\"1387\">6. What should a non-IT person learn first in data science?<\/h3><p data-start=\"1389\" data-end=\"1563\">A non-IT beginner should start with Excel, basic statistics, and data interpretation. After that, they can learn SQL, Python, data visualization, and machine learning basics.<\/p><h3 data-section-id=\"1ql05ek\" data-start=\"1565\" data-end=\"1625\">7. Can I get a job in data science without an IT degree?<\/h3><p data-start=\"1627\" data-end=\"1899\">Yes, you can get a data-related job without an IT degree if you build strong practical skills and a good project portfolio. Many learners start with roles like Data Analyst, Business Analyst, BI Analyst, or Marketing Analyst before moving into advanced data science roles.<\/p><h3 data-section-id=\"1bk1syp\" data-start=\"1901\" data-end=\"1946\">8. Is Python compulsory for data science?<\/h3><p data-start=\"1948\" data-end=\"2146\">Python is not compulsory at the very beginning, but it is highly recommended for long-term growth in data science. It is widely used for data cleaning, analysis, visualization, and machine learning.<\/p><h3 data-section-id=\"1ddf4ab\" data-start=\"2148\" data-end=\"2206\">9. What kind of projects should non-IT learners build?<\/h3><p data-start=\"2208\" data-end=\"2430\">Non-IT learners should build business-focused projects such as sales analysis, customer segmentation, HR attrition analysis, financial analysis, marketing campaign analysis, inventory analysis, and basic prediction models.<\/p><h3 data-section-id=\"lneqdn\" data-start=\"2432\" data-end=\"2484\">10. Can a non-IT person become a data scientist?<\/h3><p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<\/p><p data-start=\"2486\" data-end=\"2707\" data-is-last-node=\"\" data-is-only-node=\"\">Yes, a non-IT person can become a data scientist by learning the right skills, practicing consistently, building projects, and gaining confidence in statistics, SQL, Python, machine learning, and business problem-solving.<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_ma_el_bg_slider elementor-section elementor-top-section elementor-element elementor-element-150ea82e elementor-section-boxed elementor-section-height-default elementor-section-height-default jltma-glass-effect-no\" data-id=\"150ea82e\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"has_ma_el_bg_slider elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-335164a jltma-glass-effect-no\" data-id=\"335164a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<section class=\"has_ma_el_bg_slider elementor-section elementor-inner-section elementor-element elementor-element-7b7700c5 elementor-section-boxed elementor-section-height-default elementor-section-height-default jltma-glass-effect-no\" data-id=\"7b7700c5\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t\t\t<div class=\"elementor-row\">\n\t\t\t\t\t<div class=\"has_ma_el_bg_slider elementor-column elementor-col-33 elementor-inner-column elementor-element elementor-element-301a27a2 jltma-glass-effect-no\" data-id=\"301a27a2\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7c0209a6 jltma-glass-effect-no elementor-widget elementor-widget-image\" data-id=\"7c0209a6\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-image\">\n\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"415\" height=\"277\" src=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2022\/09\/author2.png\" class=\"attachment-large size-large wp-image-12236\" alt=\"Prateek Agrawal\" srcset=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2022\/09\/author2.png 415w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2022\/09\/author2-300x200.png 300w, https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2022\/09\/author2-150x100.png 150w\" sizes=\"auto, (max-width: 415px) 100vw, 415px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"has_ma_el_bg_slider elementor-column elementor-col-66 elementor-inner-column elementor-element elementor-element-9a5668d jltma-glass-effect-no\" data-id=\"9a5668d\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-column-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-22cb9fd7 jltma-glass-effect-no elementor-widget elementor-widget-text-editor\" data-id=\"22cb9fd7\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-text-editor elementor-clearfix\">\n\t\t\t\t<p>Prateek Agrawal is the founder and director of Ivy Professional School. He is ranked among the top 20 analytics and data science academicians in India. With over 16 years of experience in consulting and analytics, Prateek has advised more than 50 leading companies worldwide and taught over 7,000 students from top universities like IIT Kharagpur, IIM Kolkata, IIT Delhi, and others.<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Table of Contents Add a header to begin generating the table of contents Many people believe that data science is only for software engineers, coders, or people from a computer science background. This is one of the biggest myths stopping talented professionals from entering the field. The truth is simple: Can a non-IT person learn data science? Yes, absolutely. Data science is not just about writing code. It is about understanding data, asking the right questions, finding patterns, solving business problems, and communicating insights clearly. In fact, many non-IT professionals already use data in their daily work without calling it \u201cdata science.\u201d Sales teams analyze targets, finance teams study costs, HR teams review attrition, marketing teams track campaigns, and operations teams monitor performance. Data science simply gives structure, tools, and advanced techniques to do this better. So, if you are from commerce, management, economics, statistics, engineering, HR, sales, finance, operations, or even a completely different background, this blog will help you understand how you can enter the field confidently. What Does Data Science Actually Mean? Before answering Can a non-IT person learn data science, it is important to understand what data science really is. Data science is the process of [&hellip;]<\/p>\n","protected":false},"author":1001976,"featured_media":13326,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[881],"tags":[],"class_list":["post-13308","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Can a Non-IT Person Learn Data Science? A Complete Guide for Beginners - R vs Python: Which Analytics Tool Should You Choose for Data Science?<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ivyproschool.com\/blog\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Can a Non-IT Person Learn Data Science? A Complete Guide for Beginners - R vs Python: Which Analytics Tool Should You Choose for Data Science?\" \/>\n<meta property=\"og:description\" content=\"Table of Contents Add a header to begin generating the table of contents Many people believe that data science is only for software engineers, coders, or people from a computer science background. This is one of the biggest myths stopping talented professionals from entering the field. The truth is simple: Can a non-IT person learn data science? Yes, absolutely. Data science is not just about writing code. It is about understanding data, asking the right questions, finding patterns, solving business problems, and communicating insights clearly. In fact, many non-IT professionals already use data in their daily work without calling it \u201cdata science.\u201d Sales teams analyze targets, finance teams study costs, HR teams review attrition, marketing teams track campaigns, and operations teams monitor performance. Data science simply gives structure, tools, and advanced techniques to do this better. So, if you are from commerce, management, economics, statistics, engineering, HR, sales, finance, operations, or even a completely different background, this blog will help you understand how you can enter the field confidently. What Does Data Science Actually Mean? Before answering Can a non-IT person learn data science, it is important to understand what data science really is. Data science is the process of [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ivyproschool.com\/blog\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\/\" \/>\n<meta property=\"og:site_name\" content=\"R vs Python: Which Analytics Tool Should You Choose for Data Science?\" \/>\n<meta property=\"article:published_time\" content=\"2026-05-16T10:52:08+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-05-16T12:22:10+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"1920\" \/>\n\t<meta property=\"og:image:height\" content=\"1080\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Prateek Agrawal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Prateek Agrawal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"13 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\\\/\"},\"author\":{\"name\":\"Prateek Agrawal\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#\\\/schema\\\/person\\\/8010a561e914798a4419e937b20aa49b\"},\"headline\":\"Can a Non-IT Person Learn Data Science? 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Discover the key differences in data visualization, handling capabilities, speed, and ease of learning.\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/#\\\/schema\\\/person\\\/8010a561e914798a4419e937b20aa49b\",\"name\":\"Prateek Agrawal\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/7b44716c53f75a40cfd6a238640ed4bd0e72117b1789f1bea3c4fe0e43c2475a?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/7b44716c53f75a40cfd6a238640ed4bd0e72117b1789f1bea3c4fe0e43c2475a?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/7b44716c53f75a40cfd6a238640ed4bd0e72117b1789f1bea3c4fe0e43c2475a?s=96&d=mm&r=g\",\"caption\":\"Prateek Agrawal\"},\"sameAs\":[\"https:\\\/\\\/www.linkedin.com\\\/in\\\/prateekagrawal\\\/\"],\"url\":\"https:\\\/\\\/ivyproschool.com\\\/blog\\\/author\\\/dm_ivy\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Can a Non-IT Person Learn Data Science? 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Data science is not just about writing code. It is about understanding data, asking the right questions, finding patterns, solving business problems, and communicating insights clearly. In fact, many non-IT professionals already use data in their daily work without calling it \u201cdata science.\u201d Sales teams analyze targets, finance teams study costs, HR teams review attrition, marketing teams track campaigns, and operations teams monitor performance. Data science simply gives structure, tools, and advanced techniques to do this better. So, if you are from commerce, management, economics, statistics, engineering, HR, sales, finance, operations, or even a completely different background, this blog will help you understand how you can enter the field confidently. What Does Data Science Actually Mean? Before answering Can a non-IT person learn data science, it is important to understand what data science really is. Data science is the process of [&hellip;]","og_url":"https:\/\/ivyproschool.com\/blog\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\/","og_site_name":"R vs Python: Which Analytics Tool Should You Choose for Data Science?","article_published_time":"2026-05-16T10:52:08+00:00","article_modified_time":"2026-05-16T12:22:10+00:00","og_image":[{"width":1920,"height":1080,"url":"https:\/\/ivyproschool.com\/blog\/wp-content\/uploads\/2026\/05\/Can-a-Non-IT-Person-Learn-Data-Science_V01.jpg.jpeg","type":"image\/jpeg"}],"author":"Prateek Agrawal","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Prateek Agrawal","Est. reading time":"13 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/ivyproschool.com\/blog\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\/#article","isPartOf":{"@id":"https:\/\/ivyproschool.com\/blog\/can-a-non-it-person-learn-data-science-a-complete-guide-for-beginners\/"},"author":{"name":"Prateek Agrawal","@id":"https:\/\/ivyproschool.com\/blog\/#\/schema\/person\/8010a561e914798a4419e937b20aa49b"},"headline":"Can a Non-IT Person Learn Data Science? 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