This is sloppy and hides intent if you ever reference it more

These similarities below are the skills and tools that both roles use. Mainly used by both are the programming languages and tools that help to deploy a Data Science model. Depending on the company, a Data Scientist could expect to work more on deployment, or the same could be said about a Data Engineer.

Most importantly in Data Science, is the ability to communicate. You will most likely have to work with a Product Manager or stakeholder to go over weaknesses in the business before you even look at the data in your company and start your Data Science model building process.

This is also the case in higher education, where even choosing a college has become a matter of life and death. We have moved from a time when colleges were a community’s lifeblood — providing jobs, culture, and diversity of thought and experience — to a time when many college campuses have become Covid hotspots, bringing rising infection rates and fear to the communities they once enriched.

Now if you need to reference the name later, you will be doing so via a named variable vs. an index value. This works well for response data that you’ll likely know the structure of. As long as the person’s information is always in the same order, you can destructure and assign everything over and over again to avoid using index values.

Using the ** operator on the dict as you’re passing a dict to the function allows you to unpack all of the arguments successfully (instead of accidentally passing the dict object itself). Although this method does add another variable and a separate data structure, it improves overall readability when there are a larger number of arguments. Moving the function call around or referencing multiple calls to the same function with the same (or slightly tweaked) arguments now becomes infinitely easier and requires less overall modification.

If you pass a class to dir, it will list all of the attributes for that object. This includes the names of its functions. By filtering for a prefix, suffix, or included keyword in the string name, we can group the functions of this class into different categories. This allows us to “pick up” new functions whose names include a keyword and either call them all or perform other logic with them later on in the code.

Although certain formats of this indentation style might technically be allowed in PEP8, I personally do not enjoy looking at heavily indented function arguments. You are forced to move your eyes all the way over to the right, some IDEs don’t play nice with this indentation, and using this style inhibits future extensibility.

If you’re using an API that requires an API key, please keep that key a secret. If you’re not planning on uploading your code or hosting your project publicly, you should be fine, but if you are going to upload it to GitHub or host it live then take these steps to keep your API key secret.
We have moved from a time when colleges were a community’s lifeblood — providing jobs, culture, and diversity of thought and experience — to a time when many college campuses have become Covid hotspots, bringing rising infection rates and fear to the communities they once enriched.
There are lessons to be learned for organizations, leaders, and individuals. For Champlain College, all that we learned from the pandemic this fall helps to fuel our optimism about the future. The following lessons are ones we will take forward in defining what 2021 looks like on our campus:

Then when you want to use this environment variable in your code, refer to it using process.env.REACT_APP_API_KEY instead of a string containing your API key. Don’t forget to also add your .env file to your .gitignore.As covered earlier, APIs are a great tool to understand and implement. This article has set out to provide an overview of what APIs are, examples of popular APIs, and a brief tutorial on how to make requests. I hope that this article has been helpful, thanks for reading!https://medium.com/dataseries/hiding-secret-info-in-python-using-environment-variables-a2bab182eea — This is a great tutorial blog post on using environment variables in Python.

The coronavirus pandemic has transformed us from a nation that shunned discussions of death to one that receives daily mortality reports. In the face of unimaginable loss — of friends, family, jobs, and freedom — many have adopted a “hospice mentality,” a state of mind where our best days are behind us and the future is bleak.

In your project folder, create a file called .env (a file where we can store environment variables). In this file on the first line, you’re going to want to type REACT_APP_API_KEY= and then paste your API key. No quotes, no ;

For skills, these are used to query data, clean data, apply transformations, prepare data for Machine Learning algorithms, and visualize both exploratory data analysis and results of the Data Science model. Data Scientists often use platforms like Jupyter Notebook as well (or other similar ones) to perform research, including both code and comments, with a nice way to visualize and organize their work in progress.

As covered earlier, APIs are a great tool to understand and implement. This article has set out to provide an overview of what APIs are, examples of popular APIs, and a brief tutorial on how to make requests. I hope that this article has been helpful, thanks for reading!

When I started my presidency at Champlain College in Burlington, VT on July 1, our students had been sent home and the pandemic ravaged the country. Leading a college through a pandemic during a time of economic upheaval, social unrest, racial injustice, a divisive political landscape, and a climate crisis, has been the greatest test of my professional career. Yet I believe the true test of a leader is finding ways to pivot in an uncertain world and meet challenges with innovation and creativity.

Even as we approach a year of the pandemic with no end in sight, I feel optimistic about the future. And, I am not alone. A survey commissioned by Champlain College Online about career prospects, Covid-19, and the election found 66% of responders felt positive about the future. That positivity also translated into action, with two out of three respondents taking steps to improve their career prospects.

What are some of the key skills and concepts that define the role of a Data Scientist? There is plenty to discuss, so I will include some of these that I have personally worked with or have seen across several job descriptions. A Data Scientist can be defined in different ways, with differing opinions, but to me, I believe a Data Scientist is a person who employs the use of data and Machine Learning algorithms, to solve business problems efficiently. Therefore, with this definition, I will speak to the respective skills that tie in.Before we start, let’s acknowledge that these roles vary from company to company. That being said, there are still general themes to each specific role of Data Scientist and Data Engineer that differentiate them. Simply put, the skills and tools of each role can see plenty of overlap, but the concepts and goals differ greatly. I will be discussing in more detail the skills, concepts, similarities, and differences between the two positions. Please read below for a discussion on Data Science and Data Engineering; what makes them similar, and what makes them different.These concepts below are ones to keep in mind as Data Science is not just code and programming, but a role that helps to solve business problems. Efficiency and saving money go hand-in-hand, and they are especially prevalent for Data Scientists. These are useful for any role, but for Data Science, the goal is to automate a process from the benefit of a Machine Learning algorithm. In turn, this model will save money and time. You will need to know how the specific algorithms work so that you can also optimize for the best algorithm. Statistics is important to know, especially when you are A/B testing and setting up experiments for a product.

In this example, let’s assume we have the class above containing a large number of functions. Some of these functions serve a special purpose and should be dynamically accessible. We want any special function that we add to this class to be immediately picked up by the rest of our code so that it begins working right away. One way to accomplish this is simply by using dir on the containing class.

This is sloppy and hides intent if you ever reference it more

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