data science for beginners

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you’ll learn what hosting is and we’ll identify the four types of hosting available at Free. To make your website visible on the web, your website’s files and data must be physically stored on a computer that is connected to the Internet. These large high-powered computers are called web servers. Website hosts are companies that physically house several web servers in one location, or what is sometimes referred to as a data center. In addition to housing the web servers, website hosts provide the software, security, support, and bandwidth that connects your website to the internet.

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Think of a website hosting company like a shopping center that contains several individual stores. If you want to open a store at the shopping center, you can lease space in it and set up shop. Just like a shopping center, website hosting companies enable you to lease space on their web servers, where you can store your website files and make them available for visitors to view on the Internet. To accommodate a wide variety of websites and customer needs, there are a variety of hosting solutions.

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Hosting solutions are broadly categorized based on the amount of server space you need for your website files, and the monthly amount of bandwidth your site consumes. Bandwidth refers to the amount of data being transferred, or the amount of resource usage your website requires. Consider your shop again… Suppose you sell only handmade bracelets; you have a small, unique product offering, so you don’t need, nor want, to lease the same amount of space as a big department store. Instead, you could lease a smaller store in the shopping center that gives you just enough space for your goods and costs less money.

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Additionally, because you’re a small shop you don’t need a lot of extra technology or staff to help you sell your product like a department store requires. Between you and your mobile payment device, you have plenty of bandwidth to take care of your customers, and don’t need to buy any extra technology or hire more employees. Make sense? Beyond server space and bandwidth, there are other things to consider when selecting a hosting solution: your budget, ease of use or complexity of solution, the level of flexibility or customization the solution allows, as well as privacy and security features. Free offers a variety hosting solutions. To determine which hosting solution is best for you, please visit Free web Hosting.

data science for beginners

The number of rides it can provide and hence benefit from this Uber surge pricing algorithm uses data science. Let’s see how a data science process always begins with understanding the business requirement or the problem. You’re trying to solve in this case. The business requirement is to build a dynamic pricing model that takes effect. When a lot of people in the same area are requesting rides at the same time. This is followed by data collection Uber collects data such as the weather. Oracle data holidays time traffic pick up and drop location and it keeps a track of all of this. The next stage is data cleaning while sometimes unnecessary data is collected such data only increases the complexity of the problem an example is boober might collect information like the location of restaurants and cafes nearby now such data is not needed to analyze Uber surge pricing there for such data has to be removed at this step data planning is followed by date. Exploration and Analysis. The data exploration stage is like the brainstorming of data analysis. This is where you understand the patterns in your data.

the data science career opportunities in India. More specifically, we’ll talk about how you can become a data scientist in India. We’ll take a look at the latest research to help you assess your chances of landing a data scientist job. Then, we’ll focus on the education and qualifications you need to become a data scientist eligible for the job at any company. To top things off, we’ll point you in the right direction in terms of where to look for data scientist job openings in India and we’ll share some extra tips that will help you stand out from the crowd. But before we get started… We’d like to mention something else we’ve put together! – a very comprehensive data science training. The 365 Data Science program contains the full set of data science courses you need to develop the entire skillset for the job. It’s completely beginner-friendly. For example, if you don’t have any maths or statistics knowledge, we’ll teach you that first. And if you’d like to build a more specialized skillset, you can do that with courses on Time Series Analysis, Credit Risk Modeling and more.

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If you’d like to explore this further or enroll using a 20% discount, there’s a link in the description you can check out. Alright! Back to the data scientist job and its outlook in India. What do the numbers say? A recent report by The Hindu states that there are an estimated 97,000 data analytics job openings in India (Bengaluru accounts for 24% of these job openings, while Delhi/NCR for 22%). Since the data science field is progressing at an extremely fast rate, the huge demand for data science talent, especially in the Technology/IT and Industrial domain, can hardly catch up with the supply of skilled data scientists. That’s why it doesn’t come as a surprise that a significant part of the data scientists in India (more than 40%) have received a ‘data scientist’ job title within the last 24 months.

So, becoming a data scientist in India seems like a truly golden opportunity. Let’s see what that means in terms of salaries! According to, “data scientist” is the highest paying job in India. To be more precise, the average data scientist salary listed on Glassdoor is above 1,000,000 rupees per year and it could go up to 2,000,000 rupees for more experienced candidates. Of course, corporations based in large cities like Mumbai and Bangalore offer higher salaries. But keep in mind that this may soon change. Many international companies prefer to open an office in Hyderabad, as it’s much more affordable. No wonder giants like Facebook, Microsoft, Google, Amazon, and P&G already call Hyderabad their home. And that translates into even more career opportunities for data scientists in India. Now that you know for sure that “data scientist” is a rising career in India, it’s time to see what it takes to become one! Well, the education and skills required for data scientists are, to a large extent, universal, no matter which country you live in. However, to paint the most accurate picture possible, we decided to dig deep into the numbers. And guess what – we discovered some pretty interesting details about the typical data scientist in India.

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So, what education do you need to become a data scientist in India? According to our research, 50% of data scientists in India have a Master’s degree; 34% – a Bachelor’s degree; and a small 6% hold a Ph.D. Now, regarding academic background: a degree in computer studies, economics, finance, business studies, statistics, and mathematics is certainly considered an advantage. However, more and more employers are willing to weave such requirements in favor of relevant skills and real-world experience. The typical data scientist in India also speaks 2.3 languages, has taken at least 1 online course, and has posted 4 certificates on average on LinkedIn. This goes to prove the increasing importance of online data science trainings not only when it comes to learning the fundamentals, but also for acquiring the latest in-demand skills.

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This is followed by data modeling the data modeling stage basically includes building a machine learning model that predicts the Uber surge at a given time and location. This model is built by using all the insights and Trends collected in the exploration stage. The model is trained by feeding at thousands of customer records, so that it can Learn to predict the outcome more precisely. Next is the data validation stage now here the model is tested when a new customer books arrive the data of the new booking is compared with the historic data in order to check if there are any anomalies in the search prices or any false predictions, if any such anomalies are detected a notification is immediately sent to the data scientists at Uber who fix the issue. This is how Uber predicts a surge price for a given location and time the final stage of The science is deployment and optimization. So after testing the model and improving its efficiency, it is deployed on all the users at this stage customer feedback is received and if there are any issues, they are fixed here. So that was the entire data science process. Now,

Apple used data science to build a watch that monitors and individuals Health this watch collects data such as the person’s heart rate sleep cycle breathing rate activity level blood pressure Etc and keeps a record of these measures 24 bars seven. This collected data is then processed and analyzed to build a model that predicts the risk of a heart attack. So these were a few hours Locations now the question is how and why you should become a data scientist according to linkedin’s March 2019 survey a data scientist is the most promising job role in the US and it stands at number one on glass doors best jobs of 2019. Here are a couple of job trends that are collected from LinkedIn top companies like Microsoft IBM Facebook and Google have over thousand job vacancies, and this number is only going to grow. Hurley these job Trends show the vacancy of jobs with respect to jog defame coming to the salary of a data scientist the average salary ranges between a hundred thousand dollars two hundred and eighty two thousand dollars. Now remember that your salary varies on your skills your level of experience your geography and the company you’re working for here are the skills that are needed to become a data scientist. You must be skilled in statistics expertise in programming languages like our and python is a Just you’re required to have a good understanding of processes, like data extraction processing wrangling and exploration. You must also be well-versed with the different types of machine learning algorithms and how they work Advanced machine learning Concepts like deep learning is also needed you must also possess a good understanding of the different big data processing Frameworks, like Hadoop and Spark and finally, you must know how to visualize the data by using tools like Tableau and power bi now that you know what it takes to become a data scientist. It’s time to buckle up and kick start your career as a data scientist. That’s all from my side guys. If you wish to learn more about such trending Technologies

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let’s look at a few other applications of data science data science is implemented in e-commerce platforms, like Amazon and Flipkart. It is also the logic behind Netflix’s recommendation system now in all actuality Qu ality data science has made remarkable changes in today’s market. It’s applications range from credit card fraud detection to self-driving cars and virtual assistant such as City and Alexa. Let’s consider an example suppose you look for shoes on Amazon, but you do not buy it then in there. Now the next day you’re watching videos on YouTube and suddenly you see an ad for the same item you switch to Facebook there. Also, you see the same ad so how does this happen? Well this Happens because Google Tracks your search history and recommends ads based on your search history. This is one of the coolest applications of data science. In fact 35% of Amazon’s revenue is generated by product recommendation. And the logic behind product recommendation is data science. Let me tell you another sad story Scott killed in never imagined his Apple watch might save his life, but that’s exactly what happened a few months ago when he had a heart attack in the middle of the night. But how could a watch detect a heart attack any guesses? Well, it’s data science again.

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What else? 79% of data scientists in India are male. This shouldn’t discourage you, ladies, as recent data indicate that women are becoming a competitive force in the data science field. Our research also shows that data scientists in India generally have 7 or more years of working experience. However, there are plenty of data science job opportunities for skilful beginners in the field (and you can find out more about these in the super-detailed and comprehensive 365 Data Science Career Guide; the link’s in the description). That said, what are the skills you should have as a data scientist in India? The must-have skillset for a data scientist includes: proficiency in Excel, good practical knowledge of statistics and mathematics, confidence in working with visualization tools like Power BI and Tableau, and, of course – experience in scripting languages, such as SQL, Python, and R.

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data science has been a trending field of study in recent times this is because of the amount of data that we create constantly and the computing power that is available with advancements in technology but what is data science think about what happens when you book a ride on uber you open the uber app on your phone and tell the app where you want to go uber tries to find the nearest cab since then the directions to come pick you up and take you to your destination that was simple but in the background the seemingly simple task is carried out by collecting mountains of data from various sources like the phones the map and historic trends of traffic and demand for rides with this data modern-day computers are programmed to calculate the nearest driver to you the best route to your location and destination the time it will take and what you should pay in other words this is made possible with data science data science has countless other applications as well and is at the intersection of statistics data analysis and machine learning it is a combination of scientific methods models and algorithms working together to extract actionable business insights from data the u.s. faces a shortage of 140,000 to 190,000 people with deep analytical skills and 1.5 million managers who can analyze big data to make effective decisions the average salary of a data scientist is around 118 thousand dollars so still interested in data science as a profession continue on to learn more about who can become a data scientist why data scientists matter what is the data science lifecycle how big data is driving the data science revolution the career prospects for data science data is the oil of our generation beta science is becoming indispensable in today’s digitally driven world helping businesses understand consumer behavior fine tune its messaging and capture new market share to become a data scientist you don’t need to have a technical background to be a data scientist what you do need is in-depth knowledge in mathematics analytical reasoning the ability to work with large amounts of data it would also help to have a strong intellectual quest knowledge of data engineering visualization ability and excellent business acumen if you do come from a non-technical background you will likely use are if you are from a technical background then you could use Python and R it is all about understanding the possibilities and asking the right questions all in the search for the best answers every company is flooded with data and they have more data than they know what to do with so regardless of the industry vertical data science is likely to play a key role in your organization’s future success data scientists help find new ways of reducing costs entering new markets and customer demographics and launching new products or services data science also has found social and medical applications such as child welfare and predictive diagnosis as well so what does the typical data science lifecycle look like the data discovery step includes the search for different sources of relevant data structured or unstructured data then you make a decision to include specific datasets into your analysis the data preparation includes
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converting data from different sources into a common format you will standardize the data look for anomalies and make it more appropriate to work with the data science models are built using statistics logistic and linear regression differential and integral calculus among other mathematical techniques you could use tools like R Python SAS SQL tableau and so on getting things in action phase includes checking the data models for its effectiveness and ability to deliver the results you will have to verify the model works if not you have to rework on your model a data scientist needs to liaison with the various teams and be able to seamlessly communicate his findings to key stakeholders and decision makers in the organization another critical element of data science are algorithms which are a process of set of rules to solve a certain problem some of the important data science algorithms include regression classification and clustering techniques decision trees and random forests machine learning techniques like supervised unsupervised and reinforcement learning in addition to these there are many algorithms that organizations develop to serve their unique needs big data is driven by the data science revolution big data is the engine propelling the rise of data science hadoop is a popular big data framework used by most organizations Hadoop works in a distributed manner where in both the processing and storing of data is distributed on commodity hardware Hadoop is easily scalable highly economical fault tolerant and secure Hadoop consists of Hadoop distributed file system or HDFS for storing data and uses MapReduce for processing data another emerging framework is Apache spark which is touted to be up to 100 times faster than MapReduce spark stores the data in the RAM so iterative processing is fast and efficient it also deploys direct acyclic graph or daj for processing of data there is a huge demand and supply mismatch when it comes to data scientists due to this salaries of data scientists are among the best in the industry top companies like Amazon Google Facebook Microsoft in the tech space to others like ExxonMobil Visa Boeing General Electric and Bank of America are actively hiring data scientists now that you have learned about data science why data science is indispensable the data science lifecycle how it relates to big data it is time you start your journey in this promising domain and see your career soar

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