[et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_row column_structure=”1_2,1_2″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_2″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-content\/uploads\/sites\/46\/2022\/06\/DataCollab.png” title_text=”DataCollab” url=”https:\/\/www.qc.cuny.edu\/academics\/smns\/data-science\/” _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”1_2″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.17.4″ _module_preset=”default” text_text_color=”#A9A9A9″ global_colors_info=”{}”]<\/p>\n
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HOME<\/a><\/span>\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0 FREQUENTLY ASKED QUESTIONS<\/a><\/span><\/strong><\/span><\/p>\n<\/div>\n<\/div>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-content\/uploads\/sites\/46\/2022\/06\/datasc_11111.jpeg” title_text=”datasc_11111″ _builder_version=”4.17.4″ _module_preset=”default” border_color_all=”#A9A9A9″ border_style_all=”ridge” box_shadow_style=”preset4″ global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” custom_margin=”-54px||||false|false” custom_padding=”0px||||false|false” global_colors_info=”{}”][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.17.4″ _module_preset=”default” text_font_size=”16px” global_colors_info=”{}”]COURSES IN DATA SCIENCE, DATA ANALYTICS and DIGITAL HUMANITIES We offer courses from entry level to advanced. Learn more about your options below.<\/span> Entry-Level Courses in Data-related Fields \/ Applications include: <\/strong><\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”II. Mid-Level Courses and Minors” _builder_version=”4.17.4″ _module_preset=”default” border_color_bottom=”#A9A9A9″ global_colors_info=”{}” toggle_level=”h3″ toggle_font=”|700|||||||” open=”off”]<\/p>\n Mid-Level Courses in Quantitative Skills include:<\/strong><\/p>\n *<\/strong>Prerequisites apply.<\/p>\n Mid-Level Courses of Study: Minor Programs at Queens College<\/strong><\/p>\n Students may also be interested in one or more of the following minors:<\/p>\n <\/p>\n The Minor in Data Analytics [DATA-MIN]<\/strong>\u00a0(20 credits) provides the foundational skills for data literacy as defined by the\u00a0American Association of College and Universities<\/a>, and the key competencies identified by the\u00a0Business Higher Education Forum Task Force for Data Scienc<\/a>e and Analytics<\/a>\u00a0as essential for \u201cdata-enabled\u201d graduates, which are in high demand in today\u2019s data-rich job market.\u00a0Students may combine this minor with ANY major.<\/em><\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”III. Advanced: Major Courses of Study” _builder_version=”4.17.4″ _module_preset=”default” hover_enabled=”0″ border_color_bottom=”#A9A9A9″ global_colors_info=”{}” toggle_level=”h3″ toggle_font=”|700|||||||” open=”off” sticky_enabled=”0″]<\/p>\n Students with a serious commitment to developing their quantitative skills may be interested in pursuing one or more of the following courses of study:<\/p>\n NOTE: Students that major in Business Administration, Computer Science, Mathematics, or Sociology may qualify for an ACCELERATED MA<\/a><\/strong><\/em>. Students interested in Risk Management can earn a graduate certificate as an undergraduate, regardless of major.<\/p>\n Alternatively, students may create an interdisciplinary course of study<\/strong> by choosing one or more of the previous majors and combining them with one or more of the minors from the previous list.<\/p>\n Below are some examples<\/strong> of interdisciplinary courses of study in data-related fields:<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”SOFT SKILLS for DATA SCIENCE, DATA ANALYTICS and DIGITAL HUMANITIES” _builder_version=”4.17.4″ _module_preset=”default” border_color_bottom=”#A9A9A9″ global_colors_info=”{}” toggle_level=”h3″ toggle_font=”|700|||||||” open=”off”]No matter which level of data literacy you aim to achieve, it’s important to develop soft skills<\/a> and hands on experience. Take advantage of our co-curricular programs:<\/p>\n [\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" HOME\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0 FREQUENTLY ASKED QUESTIONS COURSES IN DATA SCIENCE, DATA ANALYTICS and DIGITAL HUMANITIES We offer courses from entry level to advanced. Learn more about your options below. Entry-Level Courses in Data-related Fields \/ Applications include: Computers and Computation for Accounting, BALA, Economics, and others [CSCI 12] Data Analytics [DATA […]<\/p>\n","protected":false},"author":87,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"","_et_gb_content_width":"","inline_featured_image":false,"footnotes":""},"page_category":[],"wf_page_folders":[281],"class_list":["post-10541","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/pages\/10541","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/users\/87"}],"replies":[{"embeddable":true,"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/comments?post=10541"}],"version-history":[{"count":0,"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/pages\/10541\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/media?parent=10541"}],"wp:term":[{"taxonomy":"page_category","embeddable":true,"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/page_category?post=10541"},{"taxonomy":"wf_page_folders","embeddable":true,"href":"https:\/\/www.qc.cuny.edu\/academics\/smns\/wp-json\/wp\/v2\/wf_page_folders?post=10541"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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\n[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.17.4″ _module_preset=”default” custom_margin=”-115px||||false|false” global_colors_info=”{}”][et_pb_row _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.17.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_accordion _builder_version=”4.17.4″ _module_preset=”default” hover_enabled=”0″ border_color_bottom=”#A9A9A9″ global_colors_info=”{}” sticky_enabled=”0″][et_pb_accordion_item title=”I. Entry-Level Courses” open=”on” _builder_version=”4.17.4″ _module_preset=”default” border_color_bottom=”#A9A9A9″ global_colors_info=”{}” toggle_level=”h3″ toggle_font=”|700|||||||”]<\/p>\n\n
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