In this course, you will :
- Learn the nontechnical skills that effective data scientists must cultivate in order to turn their first job into a successful, long-term career.
- Discover how to use business intelligence to provide data-driven insights to your consulting clients.
- Discover how to use data analytics to improve business decisions and gain a competitive advantage. This fast-paced introduction is ideal for executives and managers.
- Forecast economic trends using big data. Learn how to use Microsoft Excel to perform regression analysis for economic forecasting.
- Begin using Power BI. Learn how to create and share visualisations with others in your organisation using this powerful set of business analytics tools.
- Learn how anyone, from any industry, can speak data analysis language. Learn how to prepare data, visually explore it, and statistically describe it.
- Learn how to use Tableau to create, export, and share data visualisations that can provide you with actionable business insights.
- Learn how to use Microsoft Excel to create financial forecasts quickly using analytics and big data.
- Learn how to set and track KPIs in Google Analytics to improve your marketing analytics game. Learn which KPIs are most important and how they differ depending on the type of business.
- Begin to think about data visualisation more clearly and strategically. Learn how to communicate data to any audience by leveraging best practises in visualisation and design.
- covers knowledge graph tools as well as how to network databases and create a digital knowledge base
- Learn how to give end users the ability to experiment with AI and machine learning in Power BI.
- The Non-Technical Skills of Effective Data Scientists
- Business Intelligence for Consultants
- Data Analytics for Business Professionals
- Excel: Economic Analysis and Data Analytics
- Power BI Essential Training
- Data Fluency: Exploring and Describing Data
- Using Tableau to Discover Powerful Business Insights
- Financial Forecasting with Analytics Essential Training
- Marketing Analytics: Setting and Measuring KPIs
- Data Visualization for Data Analysis and Analytics
- Data Science Foundations: Knowledge Graphs
- Power BI: Integrating AI and Machine Learning