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How Aspiring Data Scientists Should Choose a Suitable Programming Language for Data Science

Posted on July 11, 2018July 11, 2018 by Dexlab

How Aspiring Data Scientists Should Choose a Suitable Programming Language for Data Science

Data science is a fascinating and one of the fastest growing fields in the world to work in. This is why it’s becoming increasingly popular for data scientists to consider the potentials of programming languages-they form an integral part of data science.

Possessing incredible skills of programming instantly pumps up the chances of bagging a high-profile data science job, whereas the novices, who have never studied programming in their entire life have to struggle hard.

However, this is not all – only a sack of all-round programming skills won’t help you grab the sexiest job of 21^st century, there are several things to consider before you set off on becoming a successful data scientist. And they are as follows:

Generality

For a true blue data scientist, it’s not enough to possess encompassing programming skills but also the aptitude for crunching numbers. Remember, a data scientist’s day is largely spent on sourcing and processing raw data for the purpose of data cleaning – no amount of smart set of programming languages or machine learning models would be of any help.

Specificity

In advanced data science, learning knows no bounds – each time you get to reinvent something new. Learn to ace a wide array of packages and modules available in a chosen language. However, the extent of the use and application is subject to the domain-particular packages you are working on.

Performance

In few cases, optimizing the performance of the codes is essential, especially when tackling huge volumes of crucial data. Compiled languages are normally faster as compared to interpreted ones; in the same way, statically typed languages are more fail-proof than dynamically typed. As a result, an apparent trade-off exists against productivity.

With all these in mind, it’s time to delve into the most popular languages used in the field of data science – let’s start with R – it’s the most powerful open source language used for a gamut of statistical and data visualization applications, including neural networks, advanced plotting, non-linear regression, phylogenetics and lot more.

Next, we can’t help but brag about an excellent all-rounder – Python – a top notch programming language choice for all types of data scientists, seasoned and freshers. A large chunk of the data science process revolves around the cutting edge ETL process – this makes Python a universal language to excel at. Google’s Tensorflow is an added bonus point.

Lastly, SQL tops rank as a leading data processing language instead of being just an advanced analytical tool. Owing to its longevity and efficiency, SQL is deemed to be one of the most powerful weapons that modern data scientist should know of.

Parting Thoughts

In the end of the discussion, we now have a set of languages to consider for excelling data science – what you need to do is comprehend your usage requirements and compare generality, specificity and performance factors. This will help you surge towards a successful career minus the complexities associated.

DexLab Analytics offers top of the line Data Science Courses in Delhi for data enthusiasts. If you are interested in a data analyst course in Noida, drop by this esteemed institute and navigate through our in-demand courses.

The blog has been sourced from –

https://medium.freecodecamp.org/which-languages-should-you-learn-for-data-science-e806ba55a81f

https://towardsdatascience.com/what-programming-language-should-aspiring-data-scientists-learn-875017ad27e0

http://bigdata-madesimple.com/how-i-chose-the-right-programming-language-for-data-science

Data Aspirants, Consider These 4 Career Options & Jazz-up Number Games!

Posted on July 9, 2018July 9, 2018 by Dexlab

Data Aspirants, Consider These 4 Career Options & Jazz-up Number Games!

Is crunching numbers your favorite hobby?

Are you interested in deciphering how many people use smartphones, regularly?

Do you feel fascinated by the way businesses use data to frame decisions?

If yes, then you are at the right place – a career, where you could leverage this inquisitiveness and knack for numbers is just carved for you. Not necessarily it has to be data science career option, but we’ve charted down top 5 career choices for the data curious you!

Data Scientist

Tagged as the sexiest job of 21^st century, data scientist jobs are irresistible. First of all, the field of data science is expanding steadfastly – IBM prediction says the demand for data scientists will increase by 28% by the end of 2020. This brings good news for job seekers, who are on toes to enter the fascinating world of data science, where the salaries are pumping up – already they have touched six figures.

The main objective of data scientists is to collect meaningful data to help businesses formulate strategic decisions. Cleaning up and structuring the data is of primary importance – followed by cutting edge tool implementation, such as algorithms, statistical models and deep learning structures – all of them aids in extracting insights out of relevant data.

Statistician

Other than data geeks, very few love the very idea of becoming a statistician. But for guys who love churning data, the role of statistician is the most fascinating in the world. They help solve the toughest problem with data, while finding and providing answers to crucial questions.

Statisticians’ aptitude for numbers knows no bounds – and the range of projects on which they work is diverse. From ascertaining unemployment rates to nabbing the discerning the effectiveness of prescription drugs to calculating the number of endangered animals living in a given area – from designing the strategies for data collection to nabbing the latest trends, statisticians need to juggle between a lot of tasks, and solve crucial problems.

Computer Scientist

The computers are lifeline of today’s businesses – so jobs related to computing power is selling like hot cakes. The field of computer science is encompassing – nerds in love with data can discover a treasure trove of career options under this umbrella term. If you are a true blue crime buff, choose computer forensics as your leading career option. Or else, are you a major computer game aficionado? Then aspire to become a game developer or architect.

Today, software developers and architects are witnessing surging demand, and most of the jobs in this technology domain help draw salaries over $100000 annually. So, what you waiting for?!

Database Administrator

Data is next to oil; of late, it’s been treated as a valuable resource. Thus, we should look for ways to keep it safe and well-protected. Database administrators are ideal for this defensive job. They not only toil to set up fortified databases but also are responsible for maintenance, model up-keeping and implementing security measures. Undeniably, it’s one of the most challenging jobs in the world of data but at the same time, it’s also the most rewarding one – at present, it ranks as the world’s #7 best technology job, according to a notable US tabloid.

Done reading? Now, data-lovers, when are you taking the next step to turn your avocation into your vocation? Pretty soon, right!

Quick Note: DexLab Analytics is offering state of the art Data Science Courses at affordable prices. For more details on Data Science Certification, visit the official page today.

The blog has been sourced from – dataconomy.com/2018/06/five-careers-to-consider-for-data-enthusiasts

How Data Science Is Getting Better, Day by Day?

Posted on July 7, 2018May 23, 2020 by Dexlab

HOW DATA SCIENCE IS GETTING BETTER, DAY BY DAY?

In the latest Star Wars movie, the character of Rose Tico – a humble maintenance techie with a talent for tinkering is relatable; her role expands and responsibilities increase as the movie gets going, just like our data scientists. A chance encounter with Finn puts her into the frontlines of action, and by the end of the movie, she’s flying ski-speeders in the new galactic civil war, one of the most critical battles in the movie – with time, her role becomes more complex and demanding, but she never quivers and embraces the challenges to get the job done.

A lot many data scientists draw similarities with Rose’s character. In the last 5 years, the job role and responsibility of data analysts has undergone an unrecognizable change – as data proliferation is increasing in capacity and complexity, the responsibility is found shifting base from dedicated consultants to cross-functional, highly-skilled data teams, proficient enough in integrating skills together. Today’s data consultants need to complete tasks collaboratively to formulate trailblazing analysis that let businesses predict future success and growth pattern, effectively.

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Quite conventionally, the intense role of prediction falls on the sophisticated crop of data scientists, while business analysts are more oriented towards measuring churn. On the other hand, intricate tasks, like model construction or natural language processing are performed by an elite team of data professionals, armed with strong engineering expertise.

Said differently, the emergence of data manipulation languages, such as R and Python is surging – owing to their extensive usage and adaptability, businesses are biased towards implementing these languages for advanced analysis. Drawing inspiration from Rose’s character, each data scientist should adapt to newer technology and expectations, and enhance expertise and skills that’s needed for the new role.

However, acing the cutting edge programming languages and tools isn’t enough for the challenge – today, data teams need to visualize their results, like never before. The insights churned out of advanced machine learning are curated for consumption by business pioneers and operation teams. Thus, the results have to be crisp, clear and creatively presented. As a result, predictive tools are being combined with effective capability of Python and R with which analysts and stakeholders are quite familiar.

The whole big data industry is changing, and the demand for skilled big data analysts is sky-rocketing. In this tide of change, if you are not relying on advanced data analysis tools and predictive analytics, you are going to lag behind. Companies that analyze data, boost decision-making, and observe social media trends – changing with time – will have immense advantages over companies that don’t pay attention to these crucial parameters.

No second thoughts, it’s an interesting time for data aspirants to make significant impacts in the whole data community and trigger fabulous business results. For professional training or to acquire new skills – drop by DexLab Analytics – their data Science Courses in Noida are outstanding.

The blog has been sourced from – dataconomy.com/2018/02/whole-new-world-data-teams

Estimator Procedure under Simple Random Sampling: EXPLAINED

Posted on June 26, 2018May 23, 2020 by Dexlab

Estimator Procedure under Simple Random Sampling: EXPLAINED

In continuation with the previous introductory blog on sampling: An ABC Guide to Sampling Theory, we will take a closer look into the concept of the estimator procedure under Simple Random Sampling with the help of mathematical examples. It will help us understand the underlying phenomenon, the manner to be precise in which the estimator function of sampling works.

Simple random sampling (SRS) is a method of selecting a sample comprising ‘n’ number of sampling units out of the population of ‘N’ number of sampling units such that every sampling unit has an equal chance of being chosen.

The Estimator Procedure under Simple Random Sampling

The process of selection of a sample under SRS (Simple Random Sampling) is random. This means, each number of the population has an equal probability of getting selected, which makes each of the observation identical and independently distributed.

The statistic chosen by the investigation of estimation of random samples need to satisfy a set of certain properties given below:

Unbiasedness
Consistency
Sufficiency
Efficiency

As a matter of fact, investigation is always about coming up with an idea regarding the population parameters based on the sample observations. The best part would be to formulate an unbiased, consistent estimator, which is also efficient. Normally, a sample mean for a set of sample observations is considered to be a very desirable estimator to form ideas about population parameters.

In detail, let’s examine the relevance of each of the properties of an estimator:

Unbiasedness of an estimator

Take a look at the below examples to understand the very idea of unbiasedness.

Example 1:

Answer:-

According to the problem, we have

Adding (1) & (2), we get,

So, from (3), we get:-

is called an unbiased estimators for .

Now, subtracting (2) & (1), we get –

Example 2:

Assume that an investigator draws a sample from this population using SRSWR. Then show that the sample mean is an unbiased estimator for the population mean.

Now, by specification we have:-

We are redefined to show that:-

L.H.S :

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Here’s How Technology Made Education More Enjoyable and Interactive

Posted on May 31, 2018May 31, 2018 by Dexlab

Here’s How Technology Made Education More Enjoyable and Interactive

Technology is revamping education. The entire education system has undergone a massive change, thanks to technological advancement. The institutions are setting new goals and achieving their targets more effectively with the help of new tools and practices. These cutting edge methods not only enhances the learning approach, but also results in better interaction and fuller participation between teachers and students.

The tools of technology have turned students into active learners; they are now more engaged with their subjects. In fact, they even discover solutions to the problems on their own. The traditional lectures are now mixed with engaging illustrations and demonstrations, and classrooms are replaced with interactive sessions in which students and teachers both participate equally.

Let’s take a look at how technology has changed the classroom learning experience:

Online Classes

No longer, students have to sit through a classroom all day. If a student is interested in a particular course or subject, he or she can easily pursue degrees online without going anywhere. The internet has made interactions between students and teachers extremely easy. From the comfort of the home, anyone can learn anything.

DexLab Analytics offers Data Science Courses in Noida. Their online and classroom training is over the top.

Free educational resources found online

The internet is full of information. From a vast array of blogs, website content and applications, students as well as teachers can learn anything they desire to. Online study materials coupled with classroom learning help the students in strengthening their base on any subject as they get to learn concepts from different sources with examples and practice enough problems. This explains why students are so crazy for the internet!

Webinars and video streaming

The facilitators and educationists are nowadays looking up to video streaming to communicate ideas and knowledge to the students. Videos are anytime more helpful than other digital communications; they help deliver the needful content, boosting the learning abilities among the learners, while making them understand the subject matter to the core. Webinars (seminars over the web) replaces classroom seminars; teachers look up to new methods of video conferencing for smoother interaction with the students.

Podcasts

Podcasts are digital audio files. Users can easily download them. They are available over the internet for a bare subscription fee. It’s no big deal to create podcasts. Teachers can easily create podcasts that syncs well with students’ demand, thus paving a way for them to learn more efficiently. In short, podcasts allow students a certain flexibility to learn from anywhere, anytime.

Laptops, smartphones and tablets

For a better learning experience overall, both students and teachers are looking forward to better software and technology facilities. A wide number of web and mobile applications are now available for students to explore the wide horizon of education. The conventional paper notes are now replaced with e-notes that are uploaded on the internet and can be accessible from anywhere. Laptops and tablets are also used to manage course materials, research, schedules and presentations.

No second thoughts, by integrating technology with classroom training, students and teachers have an entire world to themselves. Sans the geographical limitations, they can now explore the bounties of new learning methods that are more fun and highly interactive.

DexLab Analytics appreciates the power of technology, and in accordance, have curated state of the art Data Science Courses that can be accessed both online and offline for students’ benefit. Check out the courses NOW!

The article has been sourced from – http://www.iamwire.com/2017/08/technology-teaching-education/156418

Microsoft Introduces FPGA Technology atop Google Chips through Project Brainwave

Posted on May 10, 2018May 23, 2020 by Dexlab

A Change Is In the Make – due to increasing competition among tech companies working on AI, several software makers are inventing their own new hardware. A few Google servers also include chips designed for machine learning, known as TPUs exclusively developed in-house to ensure higher power and better efficiency. Google rents them out to its cloud-computing consumers. Of late, Facebook too shared its interest in designing similar chips for its own data centers.

However, a big player in AI world, Microsoft is skeptical if the money spent is for good – it says the technology of machine learning is transforming so rapidly that it makes little sense to spend millions of dollars into developing silicon chips, which could soon become obsolete. Instead, Microsoft professionals are pitching for the idea of implementing AI-inspired projects, named FPGAs, which can be re-modified or reprogrammed to support latest forms of software developments in the technology domain. The company is buying FPGAs from chip mogul, Intel, and already a few companies have started buying this very idea of Microsoft.

This week, Microsoft is back in action with the launch of a new cloud service for image-recognition projects, known as Project Brainwave. Powered by the very FPGA technology, it’s one of the first applications that Nestle health division is set to use to analyze the acuteness of acne, from images submitted by the patients. The specialty of Project Brainwave is the manner in which the images are processed – the process is quick as well as very low in cost than other graphic chip technologies used today.

It’s been said, customers using Project Brainwave are able to process a million images in just 1.8 milliseconds using a normal image recognition model for a mere 21 cents. Yes! You heard it right. Even the company claims that it performs better than it’s tailing rivals in cloud service, but unless the outsiders get a chance to test the new technology head-to-head against the other options, nothing concrete can be said about Microsoft’s technology. The biggest competitors of Microsoft in cloud-service platform include Google’s TPUs and graphic chips from Nvidia.

At this stage, it’s also unclear how widely Brainwave is applicable in reality – FPGAs are yet to be used in cloud computing on a wide scale, hence most companies lack the expertise to program them. On the other hand, Nvidia is not sitting quietly while its contemporaries are break opening newer ideas in machine learning domain. The recent upgrades from the company lead us to a whole new world of specialized AI chips that would be more powerful than former graphic chips.

Latest reports also confirm that Google’s TPUs exhibited similar robust performance similar to Nvidia’s cutting edge chips for image recognition task, backed by cost benefits. The software running on TPUs is both faster and cheaper as compared to Nvidia chips.

In conclusion, companies are deploying machine learning technology in all areas of life, and the competition to invent better AI algorithms is likely to intensify manifold. In the coming days, several notable companies, big or small are expected to follow the footsteps of Microsoft.

For more machine learning related stories and feeds, follow DexLab Analytics. It is the best data analytics training institute in Gurgaon offering state of the art machine learning using python courses.

The article has been sourced from – https://www.wired.com/story/microsoft-charts-its-own-path-on-artificial-intelligence

Evolving Logistics Scenario: The Tech-driven Future of Logistics Industry

Posted on April 27, 2018April 5, 2019 by Dexlab

Customer expectations are growing by the day; they are demanding faster and more flexible deliveries at minimum delivery costs. Businesses are being pressurized to customize their manufacturing processes as per customer demands. This is a hard slog for the logistics industry, which has to keep delivering better services but for lower prices.

The logistics industry can only achieve this through ‘digital fitness’. It has to make intelligent use of the global wave of digitization, including data analytics, automation and ‘Physical Internet’. The Physical Internet is an open global logistics system that is transforming the way physical objects are handled, moved, stored and supplied. It aims towards the replacement of current logistical models and making global logistics more efficient and sustainable. The Physical Internet promises better standardization in logistics operations, including shipment sizes, labeling and systems.

The central theme in logistics sector is collaborative working, which enables market leaders to retain dominance.

Now, let us take a look at a few tech-driven domains that will shape the future of logistics.

The future of Logistics Lies in IoT

Internet of Things has been the most innovative technology of the present era. It has the potential to revolutionize the logistics sector. The key benefits of IoT with regard to logistics are:

Real-time alerts and notifications
Automate processes that gather data from various machines
Automate vital operations like inventory management and asset tracking: With the help of IoT, companies can improve tasks like tracking orders, determining what items need to be stocked up and how certain products are performing.
Able to function without any human interventions.
Logistic companies can provide safer deliveries
Enable the regulation of temperature and other environmental factors.

IoT will be advantageous for the entire logistics sector, including fleet and warehouse management, and shipment and delivery of products. IoT can help companies dealing with cargo shipments by improving visibility in the delivery and tracking of cargo.

Warehouse Automation

Warehouse automation is set for a major overhaul. Online shopping is thriving and logistics, especially warehouse operations, need to be more refined and speedy. Warehouse operations of many e-commerce giants are undergoing a robotics makeover. According to reports, the market for logistics robotics, which had generated revenues worth 1.9 billion USD in 2016, is likely to generate sky-high revenues worth 22.4 billion USD this year.

The advancements in robotics include programming robots to pick and pack goods, load and unload cargo and at times deliver goods too. Employing robots speed up the processes of data collection, maintaining records and managing inventories. Most importantly, robots leave no room for human errors in the processes.

Blockchain Technology in Logistics

The growth of crypto-currencies like Bitcoin has popularized blockchain technology. Blockchain being a type of distributed ledger technology provides secure, traceable and transparent transactions. Blockchain technology employed by logistics firms will improve customer visibility into shipments and help prevent data breaches.

In the present times, logistics is considered the backbone of a stable economy. Thus, for India to emerge as a superpower, the logistics market needs to be developed and integrated with state-of-the-art technologies. Conducive policies and a healthy partnership between private and public sector is crucial to steer India into an era of competent and cost-effective business operations.

In times to come, automation will transform every industry. Don’t be left behind. Get an edge by enrolling for the data science and machine learning certification course at the premier data analyst training institute in Delhi– Dexlab Analytics.

How American Express Uses Data Analytics to Promote a Data-Driven Culture

Posted on April 26, 2018May 23, 2020 by Dexlab

Since 2010, American Express, with an encompassing database crossing over 100 million credit cards accounting for more than $ 1 trillion in charge volume annually, is harnessing the power of big data. Undeniably, it resulted in incredible improvements in speed and performance.

In the last four decades, the entire financial services industry has undergone a massive change, notably in the spheres of:

Electronic payments – Online payments, comprising credit and debit cards have dramatically increased over cash, globally.

E-commerce – An excessive reliance on smartphones and internet have boosted E-commerce capabilities manifold times.

With an increasing interaction between company and customers, the latter’s online and offline identity is being collaborated for an encompassing 360-degree view. This eventually drives innovation in product designing and marketing.

Formulating a Data-Driven Culture

Data analytics is like the bull’s eye of effective marketing, and servicing and risk management. Data curation and management is now a prerequisite for competitive excellence.

Since its inception, American Express flaunts transformation: the company has transformed itself from being a trivial freight forwarding business to a top notch player in payments and customized service industry. Over the years, the working mechanism of the firm has changed dramatically, and today, it is #1 small business card issuer in the whole of the US.

No matter, while the company strives to evolve, its core values remain somewhat same. Keeping their customers above anything else and behave like a good citizen are two core values of American Express that are beyond alterations. To become a successful data-driven organization, they believe in investing on technology, analytics, along with human talent, emphasizing on a proper synthesis between technology and human cognition to trigger robust growth and future success.

How American Express Stays Relevant and Fresh?

Risk 2020 – American Express envisions how an economy or marketplace might look like after a few years, and in the process, assesses the risks to combat to address the weaker issues in the economy. A comprehensive approach, including cloud, deep learning, mobile computing and AI is the solution.

Cornerstone – This is an encompassing, global big data ecosystem. The data is stored and shared with global potentialities across trusted sources. In any organization, data is the centre of attraction, and the consultants at American Express recognize the essence of innovation lies at company’s DNA and not somewhere on the top.

The data-driven culture in American Express is simple, natural and nuanced. A huge data base is created, from acquisition to customer management, which eventually needs to be shared with third parties and partners to derive insightful conclusions for better customer experience and risk assessment. “At American Express, we take our responsibility to serve customers and the public seriously, always ensuring that solutions are best-in-class and valuable to our customers,” says Ash Gupta, president, Global Credit Risk & Information Management, American Express.

“American Express’ closed-loop data allows us to analyze a large volume of real spending that can help marketers across a range of industries connect with customers and provide unique value,” he further adds.

To know more about data-driven customer experience, visit DexLab Analytics, a premier data analyst training institute in Delhi. They offer a plethora of data analyst training courses for interested candidates.

The blog has been sourced from:

https://www.forbes.com/sites/ciocentral/2018/03/15/how-american-express-excels-as-a-data-driven-culture/#5c5ed1a81635

https://digit.hbs.org/submission/american-express-using-data-analytics-to-redefine-traditional-banking/

5 Best Data Science Resources to Ace the Game of Data

Posted on April 12, 2018May 19, 2020 by Dexlab

Wondering how a data scientist makes advances in his data career? Or how does he expand his skills in the future? Reading is the most common answer; nothing helps better than keeping a close eye on the industry news. Data science is evolving at a rapid speed; to be updated with the latest innovations and technology discoveries would be the best thing to stay ahead of the curve.

If you are a newbie in this field, make sure you are well-read about the current industry trends and articulate it well to the HR heads that you are someone who is always a step ahead to consume knowledge about data science and its related fields. This helps!

A wide number of data science blogs and articles are available over the internet, but with so many options, it’s easy to feel lost. For this and more, we have compiled a comprehensive list of 5 best data science blog recommendations that would help aspiring data scientists maneuver smoothly through this sphere.

Data Elixir

For a one stop destination for all things DATA, Data Elixir is the right choice. Crafted by ex-NASA data scientist Lon Riesberg, Data Elixir offers a list-wise view of the posts; easy categorization of content is anytime preferable and renders easy search options.

Data Science Weekly

The brain child of Hannah Brooks and Sebastian Gutierrez, Data Science Weekly is the ultimate hub for recent news, well-curated articles and promising jobs related to data science. You can either sign up for their newsletter or simply scroll through their archives dated back to 2013.

The Analytics Dispatch

The Analytics Dispatch is more like a newsletter content creating hub, wherein they send weekly emails about data science related stuff to its readers. Collected, analyzed and developed by a robust team at Mode Analytics, which also happens to be an Udacity partner, the newsletters focus on practical advices on data analysis and how data scientists should work.

O’Reilly Media’s data science blog

To read some of the most amazing articles on AI and data science, make O’Reilly Media’s data science blog your best companion. The articles are curated, researched and written by influencers and data science pundits, who are technically sound and understands the advanced nuances of the field in-depth.

Cloudera

Being top notch big data software, Cloudera’s contribution to the world of data science is immense. Time to time, it publishes interesting articles, know-hows and guides on a plethora of open source big data software, like Hadoop, Flume, Apache, Kafka, Zookeeper and more.

Besides, DexLab Analytics, a pioneering analytics training institute headquartered in Gurgaon, India also publishes technical articles, amazing blogs, riveting case studies and interviews with analytics leaders on myriad data science topics, including Apache Spark, Retail Analytics and Risk Modeling. The content is crisp, easy to understand and offers crucial insights on a gamut of topics: it helps the aspiring readers to broaden their horizons.

The realms of data science are fascinating and intimidating as well; but with the right knowledge partner, carry suave data skill in your sleeves – Data Science Courses in Noida from DexLab Analytics are the best in town! Also, their Business Analytics Training Courses in Noida are worth checking for.

Some of the parts of the blog have been sourced from – http://dataconomy.com/2018/01/5-awesome-data-science-subscriptions-keep-informed/ and https://www.springboard.com/blog/data-science-blogs

Generality

Specificity

Performance

Parting Thoughts

The blog has been sourced from –

Interested in a career in Data Analyst?

Data Scientist

Statistician

Computer Scientist

Database Administrator

Interested in a career in Data Analyst?

Interested in a career in Data Analyst?

The Estimator Procedure under Simple Random Sampling

Unbiasedness of an estimator

Interested in a career in Data Analyst?

Online Classes

Free educational resources found online

Webinars and video streaming

Podcasts

Laptops, smartphones and tablets

Interested in a career in Data Analyst?

Interested in a career in Data Analyst?

The future of Logistics Lies in IoT

Warehouse Automation

Blockchain Technology in Logistics

Interested in a career in Data Analyst?

Formulating a Data-Driven Culture

How American Express Stays Relevant and Fresh?

Interested in a career in Data Analyst?

Data Elixir

Data Science Weekly

The Analytics Dispatch

O’Reilly Media’s data science blog

Cloudera

Interested in a career in Data Analyst?

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