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The Importance of Determination for New Data Scientists

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Half a year ago, I was clueless about my future. I wanted to learn a skill that could be used for a long-term career.

I saw how fast data analytics was growing in the technology and information age, and realized I could learn an in-demand skill which would equip me with the power to analyze big datasets and uncover a business’ weaknesses or missed opportunities.

I wanted to learn a skill that could be used for a long-term career.

It doesn’t matter what field you are interested in; analytics is being used everywhere to optimize daily operations. For example, to analyze the last five years of sales data looking for trends. Or to analyze real estate sector data to predict house prices, by comparing the data from nearby neighbourhoods to justify a fair market price.

I find the power of big data fascinating and am determined to learn as much as I can to keep improving, which is why I did a little bit of research and found a part-time certificate in Data Analytics, Big Data, and Predictive Analytics at Ryerson University’s Chang School of Continuing Education.

The benefit of an in-classroom course is developing companionship alongside other students who are determined and motivated to learn. This creates relationships that help when you’re stuck for hours debugging errors and feel like giving up.

There is a mixture of professionals, Ph.D.s, M.B.A.s and those with undergraduate degrees in the program, so everyone is exposed to different perspectives.

What I also found is that a lot of my learning happened beyond the classroom, and with the amount of free resources out there, you do not have to go to a school if you are determined learner.

I personally like the word determination over passion, because passion fades over time but determination does not. If you fail fifty times, you will always stand up the fifty-first time if you are determined. That is the skill data scientists need to succeed.

This blog is for self-motivated individuals who are determined to learn by themselves.

The Essentials of Big Data

From my experience, the most important things a good data scientist needs to learn are:

  1. The language of your choice, such as Python, R or SQL.
  2. A foundation in statistics, to understand what the software is doing behind the code.
  3. Practice and more practice, to solidify the wide array of materials.

Free Resources

Here are some free resources that will help you understand the basics and strengthen your foundation in data science:

  1. [Coursera] Introduction to Big Data
    This course will help you get to know what big data is.
  2. [DataCamp] Introduction to R or Introduction to Python
    Pick the analytics tool that you want to learn and feel familiar with, and the above courses will provide brief introductions to these programming languages.
  3. [Lynda] Statistics Foundation 1,2 & 3
    I recommend these courses as they will give you insights to statistical concepts. If you already have a good statistics base, they will refresh your knowledge. If you don’t have any knowledge of statistics, they will give you the fundamentals.

Conclusion

After all this introduction to the revolutionary field of data science, if you are interested and want to dig deeper, be determined to explore the field. Then be ready to take on challenges to broaden your knowledge and skill set.

#Be Determined #Keep learning

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