{"id":8129,"date":"2025-08-27T14:47:47","date_gmt":"2025-08-27T13:47:47","guid":{"rendered":"https:\/\/oderasbm.com\/?post_type=courses&#038;p=8129"},"modified":"2025-08-27T14:47:51","modified_gmt":"2025-08-27T13:47:51","slug":"applied-data-science-course-intermediate-levelbecdaim-nov-15-dec-7","status":"publish","type":"courses","link":"https:\/\/oderasbm.com\/staging\/courses\/applied-data-science-course-intermediate-levelbecdaim-nov-15-dec-7\/","title":{"rendered":"Applied Data Science Course Intermediate Level: [BEC_DA_IM] NOV 15 &#8211; DEC 7"},"content":{"rendered":"<p><strong>Certifications:\u00a0\u00a0IBM Data Analyst or IBM Data Science Professional Certificate.<\/strong><\/p>\n<p><strong>Level: Intermediate<\/strong><\/p>\n<ul>\n<li>Tools like Python, SQL, Excel, and Jupyter Notebooks<\/li>\n<li>Practical analysis, data wrangling, and dashboarding<\/li>\n<\/ul>\n<p>Ideal as a <strong>bridge between foundation and professional certification<\/strong>, especially for learners aiming at CAP or industry data roles.<\/p>\n<h3 class=\"\" data-start=\"1908\" data-end=\"1968\"><strong data-start=\"1912\" data-end=\"1968\">3. Associate Certified Analytics Professional (aCAP)<\/strong><\/h3>\n<h4 class=\"\" data-start=\"1970\" data-end=\"1994\">\u2705 <strong data-start=\"1977\" data-end=\"1994\">Requirements:<\/strong><\/h4>\n<ul data-start=\"1995\" data-end=\"2138\">\n<li class=\"\" data-start=\"1995\" data-end=\"2055\">\n<p class=\"\" data-start=\"1997\" data-end=\"2055\">Designed for entry-level professionals or recent graduates<\/p>\n<\/li>\n<li class=\"\" data-start=\"2056\" data-end=\"2108\">\n<p class=\"\" data-start=\"2058\" data-end=\"2108\">Must hold a degree in analytics or a related field<\/p>\n<\/li>\n<li class=\"\" data-start=\"2109\" data-end=\"2138\">\n<p class=\"\" data-start=\"2111\" data-end=\"2138\">No work experience required<\/p>\n<\/li>\n<\/ul>\n<h4 class=\"\" data-start=\"2140\" data-end=\"2163\">\ud83d\udcd8 <strong data-start=\"2148\" data-end=\"2163\">Exam Focus:<\/strong><\/h4>\n<ul data-start=\"2164\" data-end=\"2256\">\n<li class=\"\" data-start=\"2164\" data-end=\"2256\">\n<p class=\"\" data-start=\"2166\" data-end=\"2256\">Same seven domains as CAP, but focuses on <strong data-start=\"2208\" data-end=\"2239\">knowledge and understanding<\/strong>, not application<\/p>\n<\/li>\n<\/ul>\n<h4 class=\"\" data-start=\"2258\" data-end=\"2282\">\ud83e\udded <strong data-start=\"2266\" data-end=\"2282\">Positioning:<\/strong><\/h4>\n<ul data-start=\"2283\" data-end=\"2365\">\n<li class=\"\" data-start=\"2283\" data-end=\"2315\">\n<p class=\"\" data-start=\"2285\" data-end=\"2315\">Pre-professional certification<\/p>\n<\/li>\n<li class=\"\" data-start=\"2316\" data-end=\"2365\">\n<p class=\"\" data-start=\"2318\" data-end=\"2365\">Best for students or early-career professionals<\/p>\n<\/li>\n<\/ul>\n<h4 class=\"\" data-start=\"2367\" data-end=\"2397\">\ud83c\udfaf <strong data-start=\"2375\" data-end=\"2397\">Comparable to BCS?<\/strong><\/h4>\n<ul data-start=\"2398\" data-end=\"2606\">\n<li class=\"\" data-start=\"2398\" data-end=\"2606\">\n<p class=\"\" data-start=\"2400\" data-end=\"2606\"><strong data-start=\"2400\" data-end=\"2413\">Somewhat.<\/strong> While still <strong data-start=\"2426\" data-end=\"2442\">introductory<\/strong>, aCAP leans more toward theoretical understanding of analytics as a process. BCS is more <strong data-start=\"2532\" data-end=\"2553\">practice-oriented<\/strong> and aligned with IT\/business analysis professionals.<\/p>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><strong>Course Summary<\/strong><\/p>\n<p>The Intermediate Level focuses on applying data science methods to solve real-world problems. Participants will dive deeper into machine learning, and advanced data visualisation, and work with unstructured data. This hands-on course emphasises project-based learning and prepares learners for real-life data science tasks.<\/p>\n<p><strong>Course Outline<\/strong><\/p>\n<ul>\n<li><strong>Week 1-2: Advanced Data Visualisation<\/strong>\n<ol>\n<li>Custom visualisations with Python (Matplotlib, Seaborn)<\/li>\n<li>Data storytelling and dashboard design<\/li>\n<li>Case studies in visualisation<\/li>\n<\/ol>\n<\/li>\n<li><strong>Week 3: Machine Learning Models<\/strong>\n<ol>\n<li>Decision trees, Random forests, and K-Nearest Neighbors<\/li>\n<li>Feature engineering and model optimisation<\/li>\n<li>Hyperparameter tuning<\/li>\n<\/ol>\n<\/li>\n<li><strong>Week 4: Working with Unstructured Data<\/strong>\n<ol>\n<li>Introduction to text data and natural language processing (NLP)<\/li>\n<li>Basic sentiment analysis<\/li>\n<li>Handling large datasets (Hadoop\/Spark)<\/li>\n<\/ol>\n<\/li>\n<li><strong>Week 5-6: Predictive Analytics<\/strong>\n<ol>\n<li>Building predictive models (time series, forecasting)<\/li>\n<li>Evaluating and fine-tuning models<\/li>\n<li>Case studies in predictive analytics<\/li>\n<\/ol>\n<\/li>\n<li><strong>Week 7: Hands-on Data Science Project<\/strong>\n<ol>\n<li>Developing a data pipeline<\/li>\n<li>Presenting and defending model results<\/li>\n<li>Collaboration and feedback<\/li>\n<\/ol>\n<\/li>\n<li><strong>Week 8: Final Project Presentation<\/strong>\n<ol>\n<li>Comprehensive project incorporating learned techniques<\/li>\n<li>Peer review and feedback<\/li>\n<\/ol>\n<\/li>\n<\/ul>\n<p><strong>\u00a0<\/strong><strong>Learning Objectives<\/strong><\/p>\n<ol>\n<li>Apply machine learning techniques to real-world datasets<\/li>\n<li>Develop predictive models and evaluate their performance<\/li>\n<li>Create advanced data visualisations to communicate complex insights<\/li>\n<li>Work with unstructured data and use it in analysis<\/li>\n<\/ol>\n<p><strong>Who Should Attend<\/strong><\/p>\n<ol>\n<li>Analysts or data scientists with foundational knowledge<\/li>\n<li>Professionals looking to apply machine learning to business problems<\/li>\n<li>Teams seeking to implement data science projects in their organisations<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Certifications:\u00a0\u00a0IBM Data Analyst or IBM Data Science Professional Certificate. Level: Intermediate Tools like Python, SQL, Excel, and Jupyter Notebooks Practical analysis, data wrangling, and dashboarding Ideal as a bridge between foundation and professional certification, especially for learners aiming at CAP or industry data roles. 3. Associate Certified Analytics Professional (aCAP) \u2705 Requirements: Designed for entry-level [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":5042,"template":"","course-category":[],"course-tag":[],"class_list":["post-8129","courses","type-courses","status-publish","has-post-thumbnail","hentry","entry","has-media","owp-thumbs-layout-horizontal","owp-btn-normal","owp-tabs-layout-horizontal","has-no-thumbnails","has-product-nav"],"_links":{"self":[{"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/courses\/8129","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/courses"}],"about":[{"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/types\/courses"}],"author":[{"embeddable":true,"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/users\/1"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/media\/5042"}],"wp:attachment":[{"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/media?parent=8129"}],"wp:term":[{"taxonomy":"course-category","embeddable":true,"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/course-category?post=8129"},{"taxonomy":"course-tag","embeddable":true,"href":"https:\/\/oderasbm.com\/staging\/wp-json\/wp\/v2\/course-tag?post=8129"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}