As a data scientist, you will deal with presentations as much as you deal with numbers. This is because a rockstar data scientist is someone who doesn’t feel shy to take credit for his work. And if you are going to be one, you need to know what is data science and what are the presentation skills that you need to know in 2020.
Here are the presentation skills, you ought to master if you need to become a good data scientist:
1. Microsoft PowerPoint
Yes, this might sound surprising. But, if you are going to become a presentation guru, you ought to start by mastering good old PowerPoint.
PowerPoint not only helps you make amazing presentations but it will also be your data analytics learning path while starting your data science career. Most of the data analytics jobs specifically mention powerpoint as one of the skills required in their job description. PowerPoint is not only a simple and easy tool for people of all ages to use, but it is also a powerful tool that has managed to stay updated through the test of times.
Advantages that make PowerPoint a must-have to start your data science career:
- PowerPoint engages the audience with the help of attractive reports, bar graphs, and line charts. As the saying goes, if you cannot explain complicated topics in a simple manner for the layman, you ain’t a master in it. PowerPoint works perfectly if you are trying to get the data across to an audience member who isn’t necessarily a data nerd, in an easy and understandable format.
- Features such as PowerPoint Macros not only make a data scientist’s life easier but also required to create data visualizations as a part of data science jobs. It shows that you can use the simplest tool to convey your key points in a structured manner.
- PowerPoint also lets you easily share your content. All you need is a basic computer with Microsoft Office installed to access your content again.
Where to master PowerPoint if you’re a data science beginner:
- Edugrad: At Edugrad, we help young professionals master PowerPoint. With talented mentors by your side, you can now learn your skills at a much faster rate than self-learning. Feel free to check out our course on mastering presentation skills for data scientists here.
- YouTube: YouTube is an excellent platform to learn PowerPoint if you know where to look. There are hundreds of videos that provide quality content out there and which helps you master the subject.
- Udemy: Whilst Udemy is not a completely free platform, it can provide you a lot more depth especially when you are looking to cover all aspects of PowerPoint. Choose a course that has rave reviews and is recommended by many in the platform.
2. Take Professional Data Analytics courses:
If you ought to become a successful Data Analyst, you need to learn at least one of the programming languages (Python or R). You need to learn Data Analytics tools and Data Science algorithms to solve a real business problem. At EduGrad, we have created the complete Data Analytics course using Python in collaboration with an ex-Google team.
This is one the comprehensive data analytics courses that will be your guide to your data science career that will help you learn how to use the power of data analytics tools to load data from any source, analyze data, create beautiful data visualizations, make predictions over time and use powerful machine learning algorithms like Linear Regression.
This end to end data science certification course is designed for both beginners with no programming experience or with average or good experienced developers looking to learn Data Science.
3. Power Bi
Power Bi is an incredibly powerful data visualization tool to present statistical data. As a data analyst/scientist, you can present dashboards with incredible amounts of detail via Power Bi.
Made by Microsoft, Power Bi was built using the SSIS heritage. It literally can consume data in any format, be it Salesforce or QuickBooks or even your standard Excel online.
PowerBi is a unique data science tools that can be fully exploited by developers. It can also be used easily by someone who is proficient with Excel and is familiar with Excel’s UI.
Here is why you should use PowerBi in data science and analytics:
- You can provide amazing data visualizations and reports using data that is present either in the cloud or in the local device.
- It is supported by Microsoft and integrates really well with the Microsoft ecosystem.
- You can create open-source visualizations, thus making it developer-friendly.
- PowerBi can be embedded into your custom applications.
- It has a powerful modeling engine that can be used for myriad purposes.
- It is also fairly cheap when compared to similar software.
There are several resources online to learn PowerBi. Here are some that you ought to check out:
- Udemy: An online learning platform that provides a variety of courses at affordable prices and
- edX: A platform that you ought to check out, especially if you are looking for quality PowerBi courses.
- Books: A good book that you can start with, to master PowerBi would be “Introducing PowerBi” by Marco Russo and Alberto Ferrari. It is one of the best data science books to start data science.
- Online Webinars and Videos.
If you are someone using a Mac, iPad or iPhone, Keynote is most probably something that you use on a fairly regular basis. Keynote presentation in a Mac is a very good option to consider mastering, especially, if you are into data science doing regular business presentations.
With several interesting features such as Magic Move, you can make your presentations more aesthetic when compared to other platforms/tools.
There are several good tutorials in a medley of sites online that can teach you all about Keynote.
Tableau, as a software, lets your teammates visualize the power of your data. By letting you connect to almost any database, Tableau helps you drag and drop your datasets to create beautiful visualizations dashboards.
Here is what makes Tableau stand out:
- It is a very aesthetic tool especially when it comes to visualizing data. Be it complex computations or simple data handling, Tableau can do it all in an elegant manner.
- Easy to use for beginners. Its simple drag and drop functionalities are a key plus point for any user of the tool.
- It can handle massive amounts of data. In addition to handling huge datasets, you can also connect it live to other platforms of your choice.
- Mobile support and a very responsive UI.
- A thriving community that can help resolve your issues.
Where to start Tableau for Data Science?
- If you are a beginner, we recommend taking a course that teaches Tableau from scratch. Online e-learning sites such as Udemy, edX, Coursera, Udacity, etc.. are a good place to start.
- Tableau also has a very active community. So, never hesitate to take the help of your community members if you are stuck somewhere.
- Kaggle also has an active community that can help you master Tableau.
You can also check out active communities that are present on LinkedIn and Facebook that can help you out in your journey to ace Tableau visualizations.
At Edugrad, we train freshers and experienced professionals and help them get their dream careers, especially in fields such as data science by providing them online course, Industry curated projects, helping them to build their Github and LinkedIn profiles followed by mock interview preparation. We hope you had a good read.