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01
Feb

0

How Many And Which Programs Should I Learn For Being A Skilled Data Scientist?

To become a data scientist, you should have knowledge of a variety of programming languages, which include Python, R, Java, SQL, JavaScript, C/C++, and Scala, to name a few. But why do you need to learn these programming languages? Let’s find out the answers by taking a look at the top programs you should learn to make your career path in data science a smooth-sailing one

31
Jan

0

Navigating An Economic Downturn: How To Plan A Career Switch To Data Science

Recently, there has been a massive layoff spree by top companies such as Google, Microsoft, and Meta. As difficult as it gets for those who are going through the layoffs, it is a challenge for those who are planning to switch careers. If you are one of those who is planning to switch to a career in data science, it is important to be strategic during these times.

30
Jan

0

Comparing The Top Three RDBMS For Data Science: Microsoft SQL, MySQL, And PostgreSQL

According to the Stackoverflow community survey in 2022, the respondents were asked which database environments they have done extensive development work in over the past year, and which they want to work in over the next year. Even though below answers have a mingle of relational database management systems with the others, in this article, we will compare the top three RDBMS: Microsoft SQL, MySQL, and PostgreSQL.

26
Jan

0
the fundamentals of statistics

Ten Things That You Need To Know In Statistics: The Fundamentals of Statistics

In this post, we’re going to discuss ten essential things that you must understand to excel in statistics. These include concepts, equations, and theorems that will not only greatly help you pursue data science but prove your understanding of statistics as well.

25
Jan

0

Unlocking The Power Of Soft Skills In Data Science

Data science is a rapidly growing field that combines statistics, computer science, and domain knowledge to extract insights and predictions from data. While technical skills such as programming and machine learning are important for data scientists, soft skills -personal attributes and interpersonal abilities- are also crucial for success in this field.

24
Jan

0

The Role Of Data Science In Cybersecurity And In Protection Against Online Threats

The field of data science can play a crucial role in cybersecurity by helping to identify, analyze, and mitigate online threats. By leveraging data science techniques, organizations can analyze large datasets generated by network and security systems to identify patterns and anomalies that may indicate a potential threat. In this article, we will briefly discuss how data science can help in assuring security.

23
Jan

0

Conscious Awareness For Cyber Security

Consciousness is an important condition in terms of human life and interaction with the environment. It is the state of being aware of the individual (him/her)self and his/her environment, his/her past memories and current feelings and thoughts. In the state of consciousness, the individual is attentive and vigilant. It can perceive the stimuli in the environment faster and turn them into information.

13
Jan

0

The Most Likely Problems In Data Analysis?

As a growing number of businesses and organizations rush to unlock the value of massive amounts of data to derive high-value, actionable business insights via data analysis, they are also facing certain problems. Here are the most common problems that you’re likely to face when performing data analysis:

12
Jan

0

The Role Of Cloud Computing In The World Of The Future

When the history of science is examined, it is seen that the need for scientific studies has increased over the ages as a result of societies’ desire for innovation and their desire to find different things.[1] Societies that have internalized scientific thinking and accepted it as a way of life; They have made significant progress in production, trade, quality of services and raising the welfare level of people. In the process of scientific development, each new knowledge has led to a rapid increase in the knowledge production process as a means of producing new knowledge.