What are the prerequisites to start a Data Science career?

 


Data science is the discipline that combines math, statistics, programming, analytics, and Artificial Intelligence to derive meaningful insights from large and complicated data sets. The insights from structured and unstructured data of any format are instrumental in enhancing business growth and generating more significant leads. A Data Science Training program will educate you on the fundamental and core concepts of the field, enabling you to excel in high-level skills like machine learning algorithms, data visualization, predictive modeling, data manipulation, web scraping, etc.

Now, let us look at the different components of this technology. They are listed below

1.    Obtaining data

The first step of this discipline is to identify what kind of data you want to work with. Data may be in any format, structured or unstructured, and can be retrieved using various technologies from any relevant source. The data is then labeled and stored in databases.

2.    Cleaning data

The next step is scrubbing the obtained data and making it readable. You need to make sure there is no value missing or wrong and that the data set is consistent throughout.

3.    Analyzing data

Then comes the most critical task - analyzing the cleaned data. You need to examine the data in various ways, identify suspicious patterns, and suggest viable solutions. This step requires efficient attention to detail and problem-solving skills.

4.    Data modeling

Here, numerous complex machine learning algorithms are applied to the data. After the data is cleaned and suspicious patterns are identified, the algorithms are used to gain valuable insights through predictive modeling.

5.    Interpreting data

This is the last and final step, also the most crucial one. At this stage, you have to explain your findings through visualization tools using charts, reports, and dashboards and describe how these findings will impact the business.

Before joining Data Science Bootcamps, you will need to have a basic understanding of specific areas. The prerequisites are core aspects like:

●     Machine learning - You need to be familiar with topics associated with ML-like regression, decision tree, logistic regression, random forest, etc.

●     Modeling - Mathematical models help hasten calculations and predictions. It is also effective in identifying the most suitable algorithm according to models and in training these models.

●     Statistics - Knowledge of statistical models will guide you in diving deeper and finding better insights about the data structure to be analyzed. These insights will help you to apply proper data science techniques and to derive the best output.

●     Programming - You should be proficient in programming languages like Python, R, Java, JavaScript, C/C++, SQL, etc.

●     Databases - An all-rounded data science professional needs to have a thorough knowledge of how databases work, how to manage these databases, and how to extract data from them.

Apart from these technical skills, it is also essential for Data Science professionals to grasp soft skills like critical thinking, persuasive communication, listening, and problem-solving. With the growing amount of data, the need to analyze it and make the best out of the analysis is of utmost importance. Companies, regardless of size and industry, have started competing to get at least one step ahead. As the competition increased, the need for tech professionals skilled in the domain has also skyrocketed. A few career options for professionals in this domain are:

●     Business Intelligence Analyst

●     Data Mining Engineer

●     Data Architect

●     Data Scientist

●     Senior Data Scientist

SynergisticIT provides an inclusive learning experience that offers hands-on training in data science and data analytics. Being the Best Data Science Bootcamp in California, getting certified from this firm will land you lucrative job opportunities in reputable organizations like Google, Accenture, Facebook, Amazon, etc. So, register today to create a robust profile under the guidance of accomplished mentors!

Also, Read This Blog: What is the future of Data Scientist?
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