{"course":{"productid":34488,"modality":6,"active":true,"language":"fr","title":"Accelerating Data Engineering Pipelines","productcode":"ADEP","vendorcode":"NV","vendorname":"Nvidia","fullproductcode":"NV-ADEP","courseware":{"has_ekit":false,"has_printkit":true,"language":""},"url":"https:\/\/portal.flane.ch\/course\/nvidia-adep","objective":"<ul>\n<li>How data moves within a computer. How to build the right balance between CPU, DRAM, Disk Memory, and GPUs.<\/li><li>How different file formats can be read and manipulated by hardware.<\/li><li>How to scale an ETL pipeline with multiple GPUs using NVTabular.<\/li><li>How to build an interactive Plotly dashboard where users can filter on millions of data points in less than a second.<\/li><\/ul>","essentials":"<ul>\n<li>Intermediate knowledge of Python (list comprehension, objects)<\/li><li>Familiarity with pandas a plus<\/li><li>Introductory statistics (mean, median, mode)<\/li><\/ul>","outline":"<p><strong>Introduction\t<\/strong>\n<\/p>\n<ul>\n<li>Meet the instructor.<\/li><li>Create an account at courses.nvidia.com\/join<\/li><\/ul><p><strong>Data on the Hardware Level<\/strong>\t\n<\/p>\n<ul>\n<li>Explore the strengths and weaknesses of different hardware approaches to data and the frameworks that support them:<ul>\n<li>Pandas<\/li><li>CuDF<\/li><li>Dask<\/li><\/ul><\/li><\/ul><p><strong>ETL with NVTabular<\/strong>\t\n<\/p>\n<ul>\n<li>Learn how to scale an ETL pipeline from 1 GPU to many with NVTabular through the perspective of a big data recommender system.<ul>\n<li>Transform raw json into analysis-ready parquet files<\/li><li>Learn how to quickly add features to a dataset, such as Categorify and Lambda operators<\/li><\/ul><\/li><\/ul><p><strong>Data Visualization<\/strong>\t\n<\/p>\n<ul>\n<li>Step into the shoes of a meteorologist and learn how to plot precipitation data on a map.<\/li><li>Learn how to use descriptive statistics and plots like histograms in order to assess data quality<\/li><li>Learn effective memory usage, so users can quickly filter data through a graphical interface<\/li><\/ul><p><strong>Final Project: Data Detective<\/strong>\t\n<\/p>\n<ul>\n<li>Users are complaining that the dashboard is too slow. Apply the techniques learned in class to find and eliminate efficiencies in the backend code<\/li><\/ul><p><strong>Final Review<\/strong>\t\n<\/p>\n<ul>\n<li>Review key learnings and answer questions.<\/li><li>Complete the assessment and earn your certificate.<\/li><li>Complete the workshop survey.<\/li><li>Learn how to set up your own AI application development environment.<\/li><\/ul>","summary":"<p>Explore how to employ advanced data engineering tools and techniques with GPUs to significantly improve data engineering pipelines.<\/p>\n<p><em>Please note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be cancelled and no refund will be issued, regardless of attendance.<\/em><\/p>","objective_plain":"- How data moves within a computer. How to build the right balance between CPU, DRAM, Disk Memory, and GPUs.\n- How different file formats can be read and manipulated by hardware.\n- How to scale an ETL pipeline with multiple GPUs using NVTabular.\n- How to build an interactive Plotly dashboard where users can filter on millions of data points in less than a second.","essentials_plain":"- Intermediate knowledge of Python (list comprehension, objects)\n- Familiarity with pandas a plus\n- Introductory statistics (mean, median, mode)","outline_plain":"Introduction\t\n\n\n\n- Meet the instructor.\n- Create an account at courses.nvidia.com\/join\nData on the Hardware Level\t\n\n\n\n- Explore the strengths and weaknesses of different hardware approaches to data and the frameworks that support them:\n- Pandas\n- CuDF\n- Dask\nETL with NVTabular\t\n\n\n\n- Learn how to scale an ETL pipeline from 1 GPU to many with NVTabular through the perspective of a big data recommender system.\n- Transform raw json into analysis-ready parquet files\n- Learn how to quickly add features to a dataset, such as Categorify and Lambda operators\nData Visualization\t\n\n\n\n- Step into the shoes of a meteorologist and learn how to plot precipitation data on a map.\n- Learn how to use descriptive statistics and plots like histograms in order to assess data quality\n- Learn effective memory usage, so users can quickly filter data through a graphical interface\nFinal Project: Data Detective\t\n\n\n\n- Users are complaining that the dashboard is too slow. Apply the techniques learned in class to find and eliminate efficiencies in the backend code\nFinal Review\t\n\n\n\n- Review key learnings and answer questions.\n- Complete the assessment and earn your certificate.\n- Complete the workshop survey.\n- Learn how to set up your own AI application development environment.","summary_plain":"Explore how to employ advanced data engineering tools and techniques with GPUs to significantly improve data engineering pipelines.\n\nPlease note that once a booking has been confirmed, it is non-refundable. This means that after you have confirmed your seat for an event, it cannot be cancelled and no refund will be issued, regardless of attendance.","skill_level":"Beginner","version":"1.0","duration":{"unit":"d","value":1,"formatted":"1 jour"},"pricelist":{"List Price":{"US":{"country":"US","currency":"USD","taxrate":null,"price":500},"DE":{"country":"DE","currency":"EUR","taxrate":19,"price":500},"AT":{"country":"AT","currency":"EUR","taxrate":20,"price":500},"SE":{"country":"SE","currency":"EUR","taxrate":25,"price":500},"SI":{"country":"SI","currency":"EUR","taxrate":20,"price":500},"GB":{"country":"GB","currency":"GBP","taxrate":20,"price":420},"IT":{"country":"IT","currency":"EUR","taxrate":20,"price":500},"CA":{"country":"CA","currency":"CAD","taxrate":null,"price":690}}},"lastchanged":"2025-07-29T12:18:27+02:00","parenturl":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-courses","nexturl_course_schedule":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course-schedule\/34488","source_lang":"fr","source":"https:\/\/portal.flane.ch\/swisscom\/fr\/json-course\/nvidia-adep"}}