[et_pb_section fb_built=”1″ custom_padding_last_edited=”off|tablet” admin_label=”Header” _builder_version=”4.24.0″ _module_preset=”default” background_color=”#ff6d29″ background_image=”https:\/\/as.nida.ac.th\/storage\/2024\/01\/venture_02.png” custom_padding=”||0px||false|false” custom_padding_phone=”60px||||false|false” locked=”off” global_colors_info=”{%22gcid-a1027310-177f-434f-a6d4-64bc6bfc2d09%22:%91%22background_color%22%93}”][et_pb_row use_custom_gutter=”on” gutter_width=”4″ _builder_version=”4.24.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.24.0″ _module_preset=”d72c0383-6487-4f2c-ac5c-7d48a6376757″ header_font=”Chakra Petch|700|||||||” header_text_color=”#FFFFFF” header_font_size=”60px” header_line_height=”1.2em” header_font_size_tablet=”50px” header_font_size_phone=”24px” header_font_size_last_edited=”on|phone” global_colors_info=”{}”]<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.16″ _module_preset=”default” custom_padding=”||0px|||” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/as.nida.ac.th\/storage\/2024\/01\/electric-services-38.png” title_text=”electric-services-38″ _builder_version=”4.16″ _module_preset=”default” custom_margin=”|-15%|||false|false” custom_margin_tablet=”|-5%|||false|false” custom_margin_phone=”|-5%|||false|false” custom_margin_last_edited=”on|phone” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.25.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_row column_structure=”1_3,1_3,1_3″ _builder_version=”4.25.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.25.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_button button_url=”https:\/\/entrance.nida.ac.th\/registrar\/applogin.asp?” url_new_window=”on” button_text=”Application” button_alignment=”center” _builder_version=”4.26.0″ _module_preset=”default” custom_button=”on” button_text_size=”35px” button_icon=”||fa||400″ button_icon_placement=”left” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.26.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_button button_url=”https:\/\/lin.ee\/YFhNT2k” url_new_window=”on” button_text=”Chat with us” button_alignment=”center” _builder_version=”4.26.0″ _module_preset=”default” custom_button=”on” button_text_size=”35px” button_icon=”||fa||400″ button_icon_placement=”left” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][et_pb_column type=”1_3″ _builder_version=”4.25.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_button button_url=”https:\/\/as.nida.ac.th\/storage\/2024\/05\/Reference-form-PH.D.pdf” url_new_window=”on” button_text=”Reference form” button_alignment=”center” _builder_version=”4.25.0″ _module_preset=”default” custom_button=”on” button_text_size=”35px” button_icon=”h||divi||400″ button_icon_placement=”left” global_colors_info=”{}”][\/et_pb_button][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.26.0″ _module_preset=”default” width=”100%” max_width=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.25.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_tabs active_tab_background_color=”#FE6D2A” active_tab_text_color=”#FFFFFF” _builder_version=”4.26.0″ _module_preset=”default” tab_font_size=”20px” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″ custom_padding=”|||30px||”][et_pb_tab title=”Highlights” _builder_version=”4.26.0″ _module_preset=”default” body_font_size=”18px” body_ol_item_indent=”20px” global_colors_info=”{}”]<\/p>\n
Ph.D. in Data Analytics and Data Science \u2013 NIDA<\/b><\/p>\n
The Ph.D. in Data Analytics and Data Science at the National Institute of Development Administration (NIDA) is designed for scholars who aim to lead innovation in data-driven research and strategic decision-making. Building on one of Thailand\u2019s most established master\u2019s programs in data science, the Ph.D. program empowers candidates to explore cutting-edge topics across disciplines and create impact through rigorous, high-value analytics.<\/span><\/p>\n Program Highlights<\/b><\/p>\n Customized, Impact-Driven Research Pathways<\/b> [\/et_pb_tab][et_pb_tab title=”PhD requirements” _builder_version=”4.26.0″ _module_preset=”default” body_font_size=”18px” body_ol_item_indent=”20px” custom_css_free_form=”@media only screen and (max-width: 840px) {||table.responsive {||margin-bottom: 0;||overflow: hidden;||overflow-x: scroll;||display: block;||white-space: nowrap;||}||}” global_colors_info=”{}”]<\/p>\n Program Milestones and Requirements<\/span><\/p>\n NIDA\u2019s Ph.D. in Data Analytics offers two study plans:<\/span><\/p>\n The program is designed to be completed within 6 to 10 semesters.<\/span><\/p>\n Coursework for Plan 2<\/b><\/p>\n\n
<\/span>NIDA hosts one of the top-ranked data science master\u2019s programs in Thailand, known for its rigorous curriculum and industry alignment. The Ph.D. program builds upon this foundation with advanced research training and academic mentorship.<\/span><\/li>\n
<\/span>Doctoral candidates engage with real-world challenges through highly relevant and emerging domains:<\/span><\/li>\n\n
<\/span>The program offers extensive academic partnerships with leading institutions in the UK and Australia, enabling student exchange, joint research, and co-advisory opportunities with internationally recognized scholars.<\/span><\/li>\n<\/ul>\n
<\/span>Candidates work closely with faculty to tailor research agendas that respond to societal needs, industrial transformation, and government priorities in digital economy, sustainability, and technology policy.<\/span><\/p>\n\n
<\/span>Students begin research immediately upon advisor approval of their proposal, subject to further endorsement by the Ph.D. Program Committee. Additional non-credit coursework from the master\u2019s curriculum may be required at the advisor\u2019s discretion to support research readiness.<\/span><\/li>\n
<\/span>Students without a background in Statistics, Actuarial Science, or related fields must complete foundational courses from the M.S. in Applied Statistics program, as determined by the Ph.D. Committee. If necessary, students may also be required to take extra credit-bearing courses beyond the standard curriculum with approval from the dean or advisor.<\/span><\/li>\n<\/ul>\n