Data Science Certificate, Bootcamp, Master’s Degree: Which is Best for Your Career?

Introduction

Whether you’ve studied for years or are just now considering the transition, you’ll need to have the right toolset if you expect to succeed in the data science field. Rigorous and competitive, the field demands applicants stay up to speed on the latest info and data science practices.

In this guide, I’ll go over three different certification methods that can help you make a career in data science: data science certificates, data science bootcamps, and a data science master’s degree. Specifically, I’ll go over the pros and cons of each to give you a better idea of which is right for you.

Let’s jump in!

1. Data Science Certificate

A data science certificate is a professional certificate that teaches foundational data science skills. These certificates are offered by a number of universities and institutions and can theoretically aid in job recruitment across a variety of data-related IT fields (but more on that later).

Pros

There are a number of pros to obtaining a data science certificate:

· Portfolio Builder

You can’t expect to get any job in data science without a proper portfolio. A data science certificate can help you build just that. Though the certificate will provide only foundational knowledge, it will still help you lay the groundwork for a quality portfolio later on.

· Relatively Inexpensive

Compared to data science bootcamps and master’s degrees, which can run in the several thousands of dollars, data science certificates can be obtained for prices even under $500. This is great for those wishing to build their skillset and portfolios at a low cost.

· Not Time-Consuming

Some certificates can be finished in a matter of weeks (and on your own schedule). Due to the low level of rigor, individuals can expect to complete these certificates quickly and without needing to abdicate prior commitments (including work, studies, and child-rearing).

#careers #bootcamp #data-science #data #education

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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

50 Data Science Jobs That Opened Just Last Week

Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

In this article, we list down 50 latest job openings in data science that opened just last week.

(The jobs are sorted according to the years of experience r

1| Data Scientist at IBM

**Location: **Bangalore

Skills Required: Real-time anomaly detection solutions, NLP, text analytics, log analysis, cloud migration, AI planning, etc.

Apply here.

2| Associate Data Scientist at PayPal

**Location: **Chennai

Skills Required: Data mining experience in Python, R, H2O and/or SAS, cross-functional, highly complex data science projects, SQL or SQL-like tools, among others.

Apply here.

3| Data Scientist at Citrix

Location: Bangalore

Skills Required: Data modelling, database architecture, database design, database programming such as SQL, Python, etc., forecasting algorithms, cloud platforms, designing and developing ETL and ELT processes, etc.

Apply here.

4| Data Scientist at PayPal

**Location: **Bangalore

Skills Required: SQL and querying relational databases, statistical programming language (SAS, R, Python), data visualisation tool (Tableau, Qlikview), project management, etc.

Apply here.

5| Data Science at Accenture

**Location: **Bibinagar, Telangana

Skills Required: Data science frameworks Jupyter notebook, AWS Sagemaker, querying databases and using statistical computer languages: R, Python, SLQ, statistical and data mining techniques, distributed data/computing tools such as Map/Reduce, Flume, Drill, Hadoop, Hive, Spark, Gurobi, MySQL, among others.

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#careers #data science #data science career #data science jobs #data science news #data scientist #data scientists #data scientists india

Is a data science certificate worth it?

Data science arrived on the scene of the technological sector and the IT industry with an unforeseen and unprecedented rush and quickly made a big space for itself. In a few short decades it has taken over the computer science and technological industry completely.

This meteoric rise in popularity has led many people to start asking the question – “Is a data science certificate worth it?” The short and simple answer to this question is that yes, a data science certification is definitely worth it.

In this article we will go into detail about the reasons why this is so. We will also attempt to give some relevant information about the data science certification, namely the PGP in data science course.

Why to choose data science certification training?

1. One will be able to build a basic foundation of knowledge -

A very important point which a learner of data science should realize in the beginning itself is that data science is a very vast field. It is formed out of the intersection of many different fields such as mathematics, statistics, computer science, information science, IT etc. So it contains a large number of concepts and topics which are difficult to impossible to master in the beginning.

The disadvantage of trying to learn data science from a 4 year university or college program is that the learner will be taught a lot of cruft; that is, he will be taught a lot of concepts and topics which he will never actually need to use in the real world. But a data science certification course will teach him the bare minimum essentials of data science which will be relevant for his career in data science.

2. One will be able to associate with instructors possessing personal experience -

Very often it turns out to be the case that the instructors teaching the learners are academicians and PhD scientists. Over their years of study and research in the field of data science they have amassed a lot of academic knowledge about it, which they are more than willing to impart to the learners.

But they lack the practical experience which only comes from working in the industry and it shows in the lack of real-world examples and case studies in their presentations. But in a data science training course, the learners are taught by professionals with decades of experience from working in the field.

3. One will be able to make use of the latest technology stacks -

In any decent PGP in data science course the course content or the course curriculum is updated frequently to keep pace with the changes in the field of data science – namely with the most recent developments and advances. Since the instructors have been professionals in the past, they are familiar with the latest technological trends in the field and update the content accordingly.

The situation is very different in university or college programs where the wizened old professors teach the same course content for years on end.

4. One will get personal care and attention from the instuctors -

In a university or college program there are typically thousands of students enrolled in the same course. So it is near to impossible for the instructors to provide personal care and attention to the students. But in a data science certification course the instructors arrange 1-on-1 meetings with the learners on a regular basis in which the learners can get all their doubts and quries cleared.

5. One can accrue practical and hands-on experience -

Any decent data science training course always contains assignments and practical projects. These provide a means for the learners to accrue hands-on and practical experience under the guidance of the seasoned and experienced instructors.

So, is a data science certification worth it?

From the above points it can be clearly seen that a data science certification is completely worth it. Not only are there numerous benefits to taking a data science training course, but the demand for skilled and competent data scientists is rising steadily as well.

So anyone who takes a course such as a PGP in data science course will have no difficulties in finding a job in any sector or industry of his choosing.

#pgp in data science #data science certification #data science training course #data science #data science certification worth it

Data Science Certificate, Bootcamp, Master’s Degree: Which is Best for Your Career?

Introduction

Whether you’ve studied for years or are just now considering the transition, you’ll need to have the right toolset if you expect to succeed in the data science field. Rigorous and competitive, the field demands applicants stay up to speed on the latest info and data science practices.

In this guide, I’ll go over three different certification methods that can help you make a career in data science: data science certificates, data science bootcamps, and a data science master’s degree. Specifically, I’ll go over the pros and cons of each to give you a better idea of which is right for you.

Let’s jump in!

1. Data Science Certificate

A data science certificate is a professional certificate that teaches foundational data science skills. These certificates are offered by a number of universities and institutions and can theoretically aid in job recruitment across a variety of data-related IT fields (but more on that later).

Pros

There are a number of pros to obtaining a data science certificate:

· Portfolio Builder

You can’t expect to get any job in data science without a proper portfolio. A data science certificate can help you build just that. Though the certificate will provide only foundational knowledge, it will still help you lay the groundwork for a quality portfolio later on.

· Relatively Inexpensive

Compared to data science bootcamps and master’s degrees, which can run in the several thousands of dollars, data science certificates can be obtained for prices even under $500. This is great for those wishing to build their skillset and portfolios at a low cost.

· Not Time-Consuming

Some certificates can be finished in a matter of weeks (and on your own schedule). Due to the low level of rigor, individuals can expect to complete these certificates quickly and without needing to abdicate prior commitments (including work, studies, and child-rearing).

#careers #bootcamp #data-science #data #education

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