{"id":118344,"date":"2023-07-26T06:29:53","date_gmt":"2023-07-26T06:29:53","guid":{"rendered":"https:\/\/www.academy-tu.berlin\/?post_type=product&#038;p=118344"},"modified":"2023-07-26T12:23:51","modified_gmt":"2023-07-26T12:23:51","slug":"introduction-to-statistics-and-programming-for-data-science05-04-2024-17-05-2024","status":"publish","type":"product","link":"https:\/\/academy.techiecraft.de\/en\/shop\/introduction-to-statistics-and-programming-for-data-science05-04-2024-17-05-2024\/","title":{"rendered":"INTRODUCTION TO STATISTICS AND PROGRAMMING FOR DATA SCIENCE<br><span style=\"color: #000078;\">05.04.2024 &#8211; 17.05.2024<\/span>"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.20.2&#8243; _module_preset=&#8221;default&#8221; global_colors_info=&#8221;{}&#8221;][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The certificate course provides intensive instruction in the fundamentals of statistics and programming for data science.<\/p>\n","protected":false},"featured_media":114426,"template":"","meta":{"_acf_changed":false,"_et_pb_use_builder":"on","_et_pb_old_content":"The certificate course provides intensive instruction in the fundamentals of statistics and programming for data science. It covers the basics of descriptive and inferential statistics as well as the fundamentals of programming for data analysis. Participants learn how to use the R\/Python language to analyse data and create data visualizations.","_et_gb_content_width":""},"product_cat":[108,110],"product_tag":[],"acf":{"ZEITRAUM":"COURSE DATES<br><br>\r\n05.04.2024 - 17.05.2024","KURSDAUER":"COURSE DURATION<br><br>\r\n6 weeks","SPRACHE":"LANGUAGE<br><br>\r\nEnglish","STANDORT":"LOCATION<br><br>\r\nOnline","ABSCHLUSS":"CERTIFICATE<br><br>\r\nTU Berlin Certificate of Professional Education (6 ETCS)","LERNFORMAT":"FORMAT<br><br>\r\nOnline","LEHRENDE*R":"LECTURER<br><br>\r\nProf. Dr. Rand Kouatly","KOSTEN":"PRICE<br><br>\r\n4350 \u20ac <br><br>\r\nRecognized as Bildungszeit","Lernziele":"<h3 style=\"text-transform:uppercase\">Learning goals<\/h3>\r\nUpon completion of the course, participants will know how to import, export and manipulate data using R\/Python packages and understand basic statistical concepts and techniques and how to calculate them in R\/Python. They will be able to create and customize different types of plots and graphs using R visualization packages. They will be proficient in creating and customizing different types of plots and graphs using Excel as complementary tools for statistics and be able to use R\/Python to perform simple statistical analysis, hypothesis testing and data exploration. They can independently perform data cleaning, data transformation and data preparation using R\/Python and know techniques for data pre-processing, cleaning and preparation.","INHALT":"<h3 style=\"text-transform:uppercase\">Content<\/h3>\r\n<b>Week 1: Preparation for the course - Software Installation<\/b>\r\n<ul>\r\n\t<li>What are R and RStudio? What are Python and Jupyter (Notebook)?<\/li>\r\n\t<li>Installing R and RStudio \/ Python and Jupyter (Notebook)? on your personal computer<\/li>\r\n\t<li>Errors, warnings and messages<\/li>\r\n\t<li>Tips on learning to code<\/li>\r\n\t<li>Package installation<\/li>\r\n        <li>Package loading<\/li>\r\n        <li>Testing and Hello World Program<\/li>\r\n<\/ul>\r\n<b>Week 2: Introduction to Programming<\/b>\r\n<ul>\r\n\t<li>Topic 1: Data Types<\/li>\r\n\t<li>Topic 2: Basics Operations<\/li>\r\n\t<li>Topic 3: Data Structure<\/li>\r\n\t<li>Programming practice 1<\/li>\r\n<\/ul>\r\n<b>Week 3: Overview of Statistics in Programming<\/b>\r\n<ul>\r\n\t<li>Topic 4: Types of Data<\/li>\r\n\t<li>Topic 5: Exploratory Data Analysis<\/li>\r\n\t<li>Topic 6: Statistics Analytics using Excel<\/li>\r\n\t<li>Programming practice 2<\/li>\r\n<\/ul>\r\n<b>Week 4: Data Manipulation and Cleaning<\/b>\r\n<ul>\r\n\t<li>Topic 7: Data Frame operations<\/li>\r\n\t<li>Topic 8: Input and Output using R\/Python<\/li>\r\n\t<li>Topic 9: Data Reshaping<\/li>\r\n        <li>Programming practice 3<\/li>\r\n<\/ul>\r\n<b>Week 5: Data Exploration and Visualization<\/b>\r\n<ul>\r\n\t<li>Topic 10: Missing data handling<\/li>\r\n\t<li>Topic 11: Exploring and visualizing techniques<\/li>\r\n\t<li>Topic 12: Visualizing data using R\/Python<\/li>\r\n        <li>Programming practice 4<\/li>\r\n<\/ul>\r\n<b>Week 6: Capstone Project<\/b>\r\n<ul>\r\n\t<li>Applying the skills and knowledge learned throughout the course to a real-world data<\/li>\r\n\t<li>Exam Project Requirement and specification<\/li>\r\n\t<li>4 hours open consultation (Groups) \u2013 Online only<\/li>\r\n<\/ul>\r\nThe course starts with a self-learning phase in which the participants will prepare themselves for the content of the course and will be provided with the corresponding software. This will be followed by virtual classroom sessions and self-study phases. Each unit is rounded off by programming exercises.","Zielgruppe_":"<h3 style=\"text-transform:uppercase\">Target group<\/h3>\r\nThis course is designed for professionals who want to take an in-depth look at data science and to learn more about fundamentals and concepts in this field.\r\n\r\n<br><br>\r\nThis course is recognized as Bildungszeit according to paragraph \u00a7 10 (5) of the Berliner Bildungszeitgesetz (BiZeitG).","Teilnahmevoraussetzungen":"<h3 style=\"text-transform:uppercase\">Prerequisites<\/h3>\r\n<ul>\r\n        <li>English level of at least B1 (according to the European Framework)<\/li>\r\n\t<li>Prior knowledge of programming and statistics<\/li>\r\n\t<li>Basics in mathematics<\/li>\r\n\t<li>Understanding of standard Microsoft Office applications<\/li>\r\n\t<li>Laptop\/PC + headset with microphone<\/li>\r\n<\/ul>","Termine":"<h3 style=\"text-transform:uppercase\">Dates<\/h3>\r\nThe certificate course starts with a self-study from April 05 \u2013 11, 2024 which serves as preparation for the course. Thereafter, there is an intensive alternation between virtual classroom sessions, self-study and online support. \r\n<br><br>\r\n<b>Course schedule:<\/b>\r\n<ul>\r\n<li>Self-study April 05 \u2013 11, 2024 (10 hours)<\/li>\r\n<li>Virtual classroom sessions from 15:00 - 21:00 (CET):<\/li>\r\n<ul>\r\n\t<li>April 12, 2024<\/li>\r\n        <li>April 19, 2024<\/li>\r\n\t<li>April 26, 2024<\/li><\/ul>\r\n<li>Self-study April 27, 2024- May 02, 2024 (18 hours) including 4 hours of open consultation in a group or individually<\/li>\r\n<li>Virtual classroom session May 03, 2024 from 15:00 - 21:00 (CET)<\/li>\r\n<li>Self-study May 04 - 09, 2024 (18 hours) including 4 hours of open consultation in a group or individually<\/li>\r\n<li>Virtual classroom preparation for the exam May 10, 2024 (2 hours)<\/li>\r\n<li>Self-study May 11 - 16, 2024 (18 hours) including 2 hours of open office hours in groups<\/li>\r\n<li>Virtual classroom exam presentation May 17, 2024 from 15:00 - 17:00 (CET)<\/li>\r\n<br><br>\r\nThis course will also be offered in <a href=\"\/en\/shop\/introduction-to-statistics-and-programming-for-data-science04-10-2024-15-11-2024\/\"><b>October\/ November 2024<\/b><\/a>.","lehrende-r-place-holder":"<h3>LEHRENDE*R<\/h3>","LEHRENDE*R-foto":4242,"LEHRENDE*R-info":"Prof. Dr. Rand Kouatly is an international academic leader, professor and researcher with more than 20 years of experience in higher education, educational technology and corporate knowledge management as well as in professional education for managers. He also has more than 10 years of international experience as a senior project manager and consultant in various technology, market and business sectors.\r\nHe is currently the Program Director for Software Engineering at the University of Europe for Applied Sciences. From 2013-2016 he worked as a Researcher at Technische Universit\u00e4t Berlin and since 2016, has been teaching as a Guest Lecturer in Technische Universit\u00e4t Berlin programs in fields including Java, machine learning and Big Data.\r\n\r\nHe is an international scholar and expert in telecommunication engineering and software development, frontend and backend development, artificial intelligence, deep learning, artificial neural networks, including the fields of pattern recognition, audio and speech processing and speech and speaker recognition, e-learning, project management and business consultancy. In addition, he is experienced in leading small companies, start-ups, projects and team leaders. He has also taken on multiple roles such as Dean and Vice Dean, Academic Researcher and Supervisor and study program creator in various public and private universities.\r\n","Interessiert":"Interested in signing up for this course?","Kurse-teilen":"","Pdf-download":118349,"Fragen":"Oder haben Sie andere Fragen?"},"_links":{"self":[{"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/product\/118344"}],"collection":[{"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/types\/product"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/media\/114426"}],"wp:attachment":[{"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/media?parent=118344"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/product_cat?post=118344"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/academy.techiecraft.de\/en\/wp-json\/wp\/v2\/product_tag?post=118344"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}