Kolby  Wyman

Kolby Wyman

1597020075

Learning Java for Data Science

Java offers versatility, interoperability, and the chance to zip around Europe in a red vespa. Data scientists are expected to have good coding chops in Python (or R). I argue that Java should be added as a useful tool in the data science skillset.

Since 1995, Java has been sipping espresso and writing killer apps, occasionally sending a wistful glance out the cafe window. It’s probable there’s already a Java app that could help you with your work as a data scientist.

This article will help you get a sense of the essentials, understand how Java could be used to support machine learning, and check out some resources for further learning. This article does not intend to teach you the actual syntax of this versatile language. This article will not offer to buy your espresso, but Java might.

In this guide:

#programming #machine-learning #data-science #python #computer-science

What is GEEK

Buddha Community

Learning Java for Data Science
Uriah  Dietrich

Uriah Dietrich

1618449987

How To Build A Data Science Career In 2021

For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.

With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.

“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.

#careers # #data science aspirant #data science career #data science career intervie #data science education #data science education marke #data science jobs #niit university data science

Siphiwe  Nair

Siphiwe Nair

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

'Commoditization Is The Biggest Problem In Data Science Education'

The buzz around data science has sent many youngsters and professionals on an upskill/reskilling spree. Prof. Raghunathan Rengasamy, the acting head of Robert Bosch Centre for Data Science and AI, IIT Madras, believes data science knowledge will soon become a necessity.

IIT Madras has been one of India’s prestigious universities offering numerous courses in data science, machine learning, and artificial intelligence in partnership with many edtech startups. For this week’s data science career interview, Analytics India Magazine spoke to Prof. Rengasamy to understand his views on the data science education market.

With more than 15 years of experience, Prof. Rengasamy is currently heading RBCDSAI-IIT Madras and teaching at the department of chemical engineering. He has co-authored a series of review articles on condition monitoring and fault detection and diagnosis. He has also been the recipient of the Young Engineer Award for the year 2000 by the Indian National Academy of Engineering (INAE) for outstanding engineers under the age of 32.

Of late, Rengaswamy has been working on engineering applications of artificial intelligence and computational microfluidics. His research work has also led to the formation of a startup, SysEng LLC, in the US, funded through an NSF STTR grant.

#people #data science aspirants #data science course director interview #data science courses #data science education #data science education market #data science interview

Ananya Gupta

Ananya Gupta

1611381728

What Are The Advantages and Disadvantages of Data Science?

Data Science becomes an important part of today industry. It use for transforming business data into assets that help organizations improve revenue, seize business opportunities, improve customer experience, reduce costs, and more. Data science became the trending course to learn in the industries these days.

Its popularity has grown over the years, and companies have started implementing data science techniques to grow their business and increase customer satisfaction. In online Data science course you learn how Data Science deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions.

Advantages of Data Science:- In today’s world, data is being generated at an alarming rate in all time lots of data is generated; from the users of social networking site, or from the calls that one makes, or the data which is being generated from different business. Because of that reason the huge amount of data the value of the field of Data Science has many advantages.

Some Of The Advantages Are Mentioned Below:-

Multiple Job Options :- Because of its high demand it provides large number of career opportunities in its various fields like Data Scientist, Data Analyst, Research Analyst, Business Analyst, Analytics Manager, Big Data Engineer, etc.

Business benefits: - By Data Science Online Course you learn how data science helps organizations knowing how and when their products sell well and that’s why the products are delivered always to the right place and right time. Faster and better decisions are taken by the organization to improve efficiency and earn higher profits.

Highly Paid jobs and career opportunities: - As Data Scientist continues working in that profile and the salaries of different position are grand. According to a Dice Salary Survey, the annual average salary of a Data Scientist $106,000 per year as we consider data.

Hiring Benefits:- If you have skills then don’t worry this comparatively easier to sort data and look for best of candidates for an organization. Big Data and data mining have made processing and selection of CVs, aptitude tests and games easier for the recruitment group.

Also Read: How Data Science Programs Become The Reason Of Your Success

Disadvantages of Data Science: - If there are pros then cons also so here we discuss both pros and cons which make you easy to choose Data Science Course without any doubts. Let’s check some of the disadvantages of Data Science:-

Data Privacy: - As we know Data is used to increase the productivity and the revenue of industry by making game-changing business decisions. But the information or the insights obtained from the data may be misused against any organization.

Cost:- The tools used for data science and analytics can cost tons to a corporation as a number of the tools are complex and need the people to undergo a knowledge Science training to use them. Also, it’s very difficult to pick the right tools consistent with the circumstances because their selection is predicated on the proper knowledge of the tools also as their accuracy in analyzing the info and extracting information.

#data science training in noida #data science training in delhi #data science online training #data science online course #data science course #data science training

Seamus  Quitzon

Seamus Quitzon

1602637135

Learning by Doing: How to Learn Java Basics by Building Your Own Project

Java is not the hardest language to start with. So, it becomes way popular among novice developers joining the ranks of Java coders every single day. If you are reading this blog post, you might be interested in learning Java.

Java is widely used across industry, and especially in the area of Enterprise software, which results in many high paying job opportunities and makes this programming language a common language for newbies. A general promotion of it within colleges and other institutions providing a formal Computer Science education also contributes to its popularity.

However, these are not the only advantages of Java — among other things, it allows you to adopt good practices and makes it way easier to learn other languages in the future. And with no doubt, you can easily learn it if you’re following the right approach. In this post, I am going to share some of them with you.

The Importance of Practice in Programming

Beyond all doubt, practice is important and valuable. But, before we get to the advantages of hands-on experience, I want to draw your attention to one essential thing I often tell my students.

New programmers who are just learning and start implementing things, without being supervised, often end up adapting bad practices. To avoid that, especially when you are making your first steps in programming, I recommend looking for a person who will supervise you and teach you. A strong mentorship with someone engaged in a serious project, as well as communication within the community in the form of sharing code and asking for feedback, is worth the effort. Similarly, when you are applying for your first job, you want to be looking for a company with a strong team and a good leader who would be keen on investing into your learning.

Now, let’s return to practical experience. Learning by doing is different from learning by passively consuming the information. To make sure we can use all the newly acquired technology, we should put our skills to test and write tons of code. The benefits of hands-on experience are almost endless.

Efficiency and Productivity

By practicing, you get a clear understanding of what programming is. Consequently, you start doing better with each new hands-on task, complete it faster, and thus become more productive.

Even if you are not working on real-world projects yet, it’s important to get used to having deadlines. They are inextricably linked to the programming process. My recommendation is to set up your own deadlines while practicing stage and follow them as closely as possible.

#java #learn java #java code #learn java in easy way #learn java course #learn java development