Complete Excel Data Analysis Bootcamp For Beginners
What you'll learn
- Get started with using Excel for basic data processing and analysis
- Carry out analytical tasks in Excel
- Data visualisation in Excel
- Basic statistical analysis in Excel
- Access to Microsoft Excel
- Interest in data processing and analysis
If You Are…..
A business intelligence (BI) practitioner
Interested in gaining insights from data (especially financial, geographic, demographic and socio-economic data)
Excel Is Your Friend for Common Business Data Analysis Tasks
I’m Minerva Singh, and I’m an expert data scientist. I’ve graduated from 2 of the world's best universities: an MPhil from Oxford University (Geography and Environment) and a PhD holder in Computational Ecology from Cambridge University. I have several years of experience in data analytics and data visualization.
My course aims to help you start with no prior/limited exposure to data analysis and become proficient in producing powerful visualizations and analyses with Microsoft Excel. You don't need prior exposure to data analytics and visualization to start with MS Excel. So if you have struggled with Excel, worry no more. After finishing my course, you will be able to:
Read in and clean messy data in MS Excel.
Carry out common business data analytic tasks, including filtering
Carry out pre-processing and data summarization to glean insights from the data
Develop powerful visualisations with MS Excel
Carry out basic statistical analysis using MS Excel
If you take this course and it ever feels like a disappointment, feel free to ask for a refund within 30 days of your purchase, and you will get it at once. Become an expert in Data Analytics and Visualization with a new and powerful tool by taking up this course today!
Who this course is for:
- Beginner data analysts
- Students and professionals seeking to use Excel for data tasks
- Those looking to use Excel for basic data visualisations
- Those looking to use Excel for basic statistical modelling
I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year's experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics.
I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly regarded academic journals such as Remote Sensing and given guest lectures on prestigious forums such as Open Data Science Conference (ODSC).