Cloud computing is a significant trend for the big data and AI industry in 2020. Using cloud environments like AWS, Micr

Storyboards — Often in marketing, or creative pitching, the story is best conveyed via images. Using stills or videos as presentation tools helps convey the message in a stronger way, and allows the audience to feel the emotion and depth of the communication.

If the audience is trying to read information from a slide during a presentation, you are wasting precious time for both parties and can often come across as ill-prepared.

This is where we confuse presentation materials with longer, more detailed proposals or formal documents. A slide deck is NOT supposed to be a detailed document of information.

If you have a more detailed set of information that needs to be conveyed along with or post a presentation, use other means. If it is reading materials, the audience must be aware of before the discussion, send it via email or hard copies beforehand. Alternately, if there are more details to a proposal or a pitch you are presenting, prepare a separate set of documents for the audience that you can hand out or send to them via email later for further review.

In software projects, data scientists often need to deliver more than some machine learning modules in the backend. There is increasing demand from the employers that data scientists need to put the machine learning and analytics codes into production. Data scientists typically need to work with programming languages like Python, R, Java, and Scala. They also need to integrate the code with the frontend and deploy the software modules in big data production environments. Therefore, Full Stack Development is one of the most crucial software skills that data scientists need.

Statistics — Data and statistics are most clearly communicated via tables and charts and can be done well via slides eg. “I believe the market for social media marketing will rise exponentially over the next five years.” A bar chart showing a trend projection is useful here to show the trajectory of the growth you are talking about, and a quick glance towards it will communicate the message.

Spot-on formatting — The good and bad thing about presentations is that everything is on a large screen. This also means that the smallest of errors, misaligned text, inconsistent font sizes, everything is very visible.

Every single bit of a slide deck should be created in coherence with the script of your presentation. It essentially is meant to engage the sense of sight in addition to the sense of hearing beyond the presenter’s expressions and body language. Slides should act as something that visually represents what words cannot fully explain or is better remembered when seen vs. heard.

Highlights or Summaries — Putting short and punchy bullets simply as headers or placeholders on a slide can help summarize the overall message. This, when supplemented by the presenter’s explanation can often help the audience build a recall around the core of the messaging.

Within the computer programming skills required for data scientists, object-oriented programming (OOP) has an important place. While programming languages like Python and Java make it so easy s to comply with major OOP principles yet, data scientists need to understand the concepts related to OOP (such as objects, attributes, methods, and inheritance) to work in real-world software projects.

Computer programming is probably the most critical part of a data science job. Programming skills are one of the crucial abilities required for data scientists to change turn the raw data into an effective analytics software user experience. That’s why data scientists need to be proficient in more than one programming language.

I am sure you have at one point or another. That, in itself, is the biggest warning sign of a cardinal sin of presentation. We often are guilty of wanting to include every last bit of detail into a presentation deck.

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red by the expression glass cannon. Using the glass dispersion shader from before, I re-skinned one of the in-game gun models. For the background, I layered one of the maps behind the gun model to match the perspective of the player.

The ability to work with structured and unstructured database technologies is also a necessity for data scientists within software projects. These database technologies can include SQL databases like PostgreSQL or NoSQL databases like MongoDB. Databases are so widely used in any software system that there is almost no escape from data science projects. There are also advanced big data technologies like Spark and Hive that enable working with Hadoop clusters.

Make sure that your slide deck is serving as a tool to help emphasize points you are looking to make to your audience. Your presentation relies on your marketing and pitching skills and not on the words and images you have on your slide deck.