{"id":462,"date":"2026-03-26T11:02:51","date_gmt":"2026-03-26T11:02:51","guid":{"rendered":"https:\/\/socs.binus.ac.id\/data-science\/?p=462"},"modified":"2026-03-27T03:14:44","modified_gmt":"2026-03-27T03:14:44","slug":"year-1-skills","status":"publish","type":"post","link":"https:\/\/socs.binus.ac.id\/data-science\/2026\/03\/26\/year-1-skills\/","title":{"rendered":"Year 1 \u2014 Foundations of Data Science"},"content":{"rendered":"
\n

Your first year is where it all begins. Before building models or writing algorithms, you need to understand what data science actually is<\/em> \u2014 and learn to see the world through data. In Year 1, you’ll develop the mindset and core skills that every great data scientist carries: the ability to ask the right questions, explore messy data with confidence, and turn raw numbers into stories that drive decisions.<\/p>\n

By the end of Year 1, you’ll be comfortable working with real datasets, creating compelling visualizations, and communicating insights to audiences who don’t speak “data.”<\/p>\n

What You’ll Be Able to Do<\/h3>\n
\n

\u2192<\/span>Frame a data science problem and map out a solution approach<\/p>\n

\u2192<\/span>Explore, clean, and understand datasets using Python<\/p>\n

\u2192<\/span>Identify patterns, distributions, and relationships in data<\/p>\n

\u2192<\/span>Build visualizations that reveal insights \u2014 not just display numbers<\/p>\n

\u2192<\/span>Tell a data story that connects analysis to real-world impact<\/p>\n<\/p><\/div>\n

Data Science Courses<\/h3>\n\n\n\n\n\n\n
Course<\/th>\nWhat You’ll Learn<\/th>\nKey Skills<\/th>\n<\/tr>\n<\/thead>\n
Introduction to Data Science<\/strong><\/td>\nUnderstand the data science landscape, how projects are structured, and how data science creates value across industries \u2014 from healthcare to finance to e-commerce.<\/td>\nProblem framing, data science methodology, use-case evaluation<\/td>\n<\/tr>\n
Data Mining and Visualization<\/strong><\/td>\nDive into real datasets through Exploratory Data Analysis (EDA). Learn to handle missing values, detect outliers, understand distributions, and build visualizations that communicate findings clearly.<\/td>\nPython (pandas, seaborn, Bokeh), EDA, data quality assessment, feature discovery, visual storytelling<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Beyond the Data Science Courses<\/h3>\n

Year 1 also builds the mathematical and computational foundations you’ll rely on throughout the program \u2014 discrete mathematics, calculus, algorithm design, and programming fundamentals. These aren’t separate from data science; they’re the language it’s written in.<\/p>\n

Year 1 is where curiosity meets structure. You’ll finish it ready to move from “what is data science?” to “let me build something with it.”<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Your first year is where it all begins. Before building models or writing algorithms, you need to understand what data science actually is \u2014 and learn to see the world through data. In Year 1, you’ll develop the mindset and core skills that every great data scientist carries: the ability to ask the right questions, […]<\/p>\n","protected":false},"author":709,"featured_media":471,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-462","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-courses"],"_links":{"self":[{"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/posts\/462","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/users\/709"}],"replies":[{"embeddable":true,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/comments?post=462"}],"version-history":[{"count":1,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/posts\/462\/revisions"}],"predecessor-version":[{"id":463,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/posts\/462\/revisions\/463"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/media\/471"}],"wp:attachment":[{"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/media?parent=462"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/categories?post=462"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/socs.binus.ac.id\/data-science\/wp-json\/wp\/v2\/tags?post=462"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}