Time with parents — our roots, with the life partner — chosen companions for the journey, with children — our future, wi

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.

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.

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.

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.

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.

At 44 then, I felt I must surely stop to take stock. Redefine my ambitions, my paradigms, chart new paths for the coming years. Make the most of how many ever years I have left in this journey. But as I look back now, another 10 years on, all that I planned never happened. The universe had its own plans for me and that is what played out. You can only play with the hand dealt out to you.

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.

You can connect to their joys, successes, trials and tribulations. At the time it made me see my twenty odd years, since the completion of my education, in new perspectives. My journey thus far — the joys, the struggles, the wins, the love.

Is it about Omegas, LV bags, Matchu Pitchu, careers, bank balances far in excess of our needs… The pursuit of wealth seems hollow and meaningless. Though frankly all of us mindlessly and doggedly don’t give up. The flip side of course is that a certain minimum amount of wealth is needed to simply survive. For the practical needs — house, food, health, education. Not to forget that drink at the end of a hard day.

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.

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.

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ust say that these titles are not fixed and may change in the future. Also, some roles may overlap and have more or fewer responsibilities based on the company hiring. However, this article should help you explore the top 10 data science roles for the most part.

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.

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.

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.