PYTHON05MTMaster ClassMT-PYTHON051.0<ul> <li>Data preparation</li><li>Data transformation</li><li>Quality evaluations</li><li>Analysis</li><li>Data analysis applications</li><li>Introduction to Machine Learning and AI</li></ul><p>Course <span class="cms-link-marked"><a class="fl-href-prod" href="/swisscom/en/course/masterclass-python03"><svg role="img" aria-hidden="true" focusable="false" data-nosnippet class="cms-linkmark"><use xlink:href="/css/img/icnset-linkmarks.svg#linkmark"></use></svg>Master Class: Advanced Python (Associate Training) <span class="fl-prod-pcode">(PYTHON03)</span></a></span> or equivalent knowledge</p><p>Data analysts, business analysts, data engineers, BI specialists, database specialists, Excel analysts</p><ul> <li>Basics of Numpy <ul> <li>What this package can do</li><li>Which data analyses are possible</li></ul></li><li>Introduction to pandas <ul> <li>Pandas Data Structures</li><li>Functionality</li><li>Which data analyses are possible and useful with pandas</li></ul></li><li>Loading and saving data <ul> <li>Practical handling of the most important file formats</li><li>Efficiency, performance and reliability</li></ul></li><li>Prepare and clean up data <ul> <li>Dealing with missing data</li><li>Data transformation</li></ul></li><li>Linking, combining and transforming data</li><li>Visualization</li><li>Aggregation and grouping of data</li><li>Time series</li><li>Pandas for advanced learners</li><li>Modelling Libraries</li><li>Examples from data analysis</li><li>Overview learning models with scikit</li></ul>- Data preparation - Data transformation - Quality evaluations - Analysis - Data analysis applications - Introduction to Machine Learning and AICourse Master Class: Advanced Python (Associate Training) (PYTHON03) or equivalent knowledgeData analysts, business analysts, data engineers, BI specialists, database specialists, Excel analysts- Basics of Numpy - What this package can do - Which data analyses are possible - Introduction to pandas - Pandas Data Structures - Functionality - Which data analyses are possible and useful with pandas - Loading and saving data - Practical handling of the most important file formats - Efficiency, performance and reliability - Prepare and clean up data - Dealing with missing data - Data transformation - Linking, combining and transforming data - Visualization - Aggregation and grouping of data - Time series - Pandas for advanced learners - Modelling Libraries - Examples from data analysis - Overview learning models with scikit3 days3290.003290.003290.0011410.002550.003290.003290.002260.00