Edure Assessment Test
Whether you are thinking of jumping into Python Development or looking out for a career in Data Science? In anyway we are excited to share with you our hand-picked collection of the best Python libraries. Well, we all know that Python offers an awesome choice of open-source libraries for Data science. So turn your programming into a scientific computing language to scientific data analysis and modeling tool with the best Python libraries!
The Python offers an awesome choice of open-source libraries for Data science and so we are! Our wise faculties with their expertise will make you a skilled full-stack Python developer. Learn the interactive coding with Edure!
Scikit-Learn is considered as one of the best Machine Learning libraries for working with complex data and most popular among ML libraries for classical ML algorithms. It contains numerous number of algorithms for implementing standard machine learning and data mining tasks, such as reducing dimensionality, classification, regression, clustering and model selection, while also offering features like Cross-validation, Unsupervised learning algorithms and Feature extractions. It would be a great tool to start out with ML.
Numpy as being another machine learning library, it allows data scientists to turn computing language using python into a powerful scientific analysis and modelling tool. Libraries like TensorFlow uses Numpy internally for better performance in multiple operations. This versatile library lets you perform multi-dimensional arrays effortlessly on various generic data.
Like the name suggests, Tensorflow is a framework that associate in defining and running computations involving tensors. It works like a computational library for writing new algorithms and is widely used in applications for machine learning. Plus, TensorFlow is optimized for speed and it uses techniques like XLA for quick linear algebra operations, which makes it accessible to visualize every part of a graph which is not an option in Numpy or SciKit. So, if you want to work on a machine learning project in Python, then you should consider choosing TensorFlow.
Keras is another high-level machine learning library which allows a easy and fast prototyping. It provides an easier mechanism to build and design a Neural Network. The most amazing factor about Keras is that it offers efficiency to compile models, process data sets, build visualization and much more. Just like Numpy, Keras is also used internally by libraries like TensorFlow and Theano. As being modular in nature, Keras is flexible and apt for building more complex models and innovative research. Those who are looking for work on a deep learning project, Keras is the best library to choose.
PyTorch is recently gaining attention among the machine learning developers due to its rich Application Programming Interface to solve issues related to neural networks. It is primarily based on Torch, which allows program developers to execute tensor computations and dynamic computational graphs automatically. Above all, it can be used internally with other libraries and packages like Cython and Numba. As being used in NLP, Pytorch is outplaying than TensorFlow in many ways.
Just like its name suggests, LightGBM is literally light and fast. It is actually designed to work fast and efficiently to implement methods and models like elementary models and decision trees. Unlike any other machine learning libraries it is fast, user-friendly, handle large-scale data and highly scalable. LightGBM provides high performance gradient boosting frameworks which makes it popular among developers.
Eli5 is a machine learning library build to help overcome challenges like debug machine learning classifiers and explain their predictions. It is designed to track the working process of an algorithm and offers build-in support for several ML frameworks. Moreover, it helps to implement several algorithms for inspecting black-box models and supports other libraries like Scikit-learn, LightGBM and many more.
SciPy is specifically designed for scientific and technical computing to work with NumPy arrays. It offers many user-friendly and fast N-dimensional array manipulation, while it is easy to use. So if you want to work on a project to manipulate numbers, then give SciPy a try!
Theano powers you to evaluate mathematical expressions efficiently through its multi-dimensional arrays and large-scale computing, along with features like speed and stability optimization and dynamic C code generation. Well, it is build on the top features of NumPy and Theano and considered as one of the fast Python Deep Learning Libraries. It was designed to execute all types of computation that requires large neural network algorithms used in Deep Learning.
If you are looking to work on a data manipulation and analysis project then you Pandas would be an apt choice for you! Pandas offers data structures and operations for manipulating numerical tables and time series. This open source library in Python is considered the finest for its features such as high-performance and easy-to-use, while it uses most of the functionalities of NumPy.
With these enriched collection of industry-standard Python libraries, you can learn to carry out complex mathematical computations, manipulate Dataframes and build complicated-dynamic models seamlessly.
You might be wondering about 'What's the next trend in Artificail Intellience?' The concept of AI has been around us for many decades, yet it only became a part of our real-world after 1950, until its true potential was discovered. Now with the new phase of technology revolution is at hand we can soon see ourself walking and networking among the AI robots. In short, the world is literally shifting from Robots to Machine learning to Deep Learning. Although the AI technology has been here for long but the field yet to be explored deeply. Along with more deep research and study on the various potrntials of ANN, we will soon see a new phase of AI automation reshaping our future. In simple words, the age of AI autonomy is no longer a distant future!
In the present scenario, Artificial Intelliegence is widely spreading across every industry, even tech giants like Google, Facebook, Amazon are making large scale investments in AI technology, With the new developemnts making headlines everyday, we will soon see the advancement and adoption of AI technology on different models across various industries by 2025. Well, for now, let's have a look at the top significant Artifical Intelligence Trends of 2019:
- 1. AI enabled chips
Embrase the new AI hardware trend, that will put the power of Neural Networks in the Palm of you Hand! The major smartphone manufacturers like iPhone, Huawei, Samsung, Qualcomm have unleashed the power of AI enabled chips through their smart products. But you might be wondering about 'What does this new AI hardware accelerated smartphones can do that weren't possible in the past? Well, what does this new generation AI chip can do is that it will make your smart device smarter than ever before! In simple words, it will make your device more efficient by reducing power consumption, increase battery life, allow onboard device processing and lower response time vs offloading cloud computing. Hold tight, because this new era has just begun to unleash its potential!
- 2. Evolution of AI with IoT
The convergence of AI with IoT is a new phase of evolution in this data driven world! but this thought have might put you in dilemma that 'how the convergence of IoT and AI going to change the standards?' Well, the combination has the capability to unlock the potential that we have never seen before. The emerging AI technology has the potential to create new and much more improved business opportunities through the smart tasks like voice recognition, language translation, decion-making, while Internet of Things (IoT) let interconnect a chain of devices that transfer data over a network; so you can think if AI is coupled with IoT, we can create something that is beyond any human imagination. Well, it's just a story line, the potential just begun to be unleashed!
- 3. Automation
An accurate definition of Automation would be like this 'a simple transfer or shift of tasks from Man to Intelligent Machine! Even though the Automation and AI are not new to us, and yet only recently, we have started to push the limitations of machine's capability when it is coupled with AI; paved the path for the era of Intelligent Automation. Today, the Intelligent Machines are capable of doing of their own which we believed to be a distant future; from automated self driving cars to automated checkouts in Amazon grocery store, we are now surrounded by the new generation machines.
- 4. Deep Learning
Even after mastering the basics of artificial intelligence and artificial neural networks, yet developers are struggling to figure out the true potential of Deep Learning; in other words, 'the potentials of Deep Learning seems boundless'. Even the scientist described the design of neural network architectures as more art than science! Deep Learning may be an application of AI yet it has more powerful potentials to unleash, or we can even say that the power of Deep Learning with Neural Networks and GPUs are driving powerful new opportunities for AI.
- 5. Cloud Computing
There had been major technological development globally which had transformed our era fro web search to digital era, where one such development was 'Cloud Computing'. And the technology has found an easy adoption and acceptance in the real world, even Tech giants like Google, Facbook, Amazon has already unraveled its power into their business. As for now, Cloud Computing plays a major role in the advance evolution of digital technology.
Get ready for the arrival of a new future with AI![post_title] => 5 Top AI Trends [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => 5-top-ai-trends [to_ping] => [pinged] => [post_modified] => 2019-05-03 13:40:19 [post_modified_gmt] => 2019-05-03 13:40:19 [post_content_filtered] => [post_parent] => 0 [guid] => http://edure.in/?p=244 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 229 [post_author] => 1 [post_date] => 2019-04-26 11:16:11 [post_date_gmt] => 2019-04-26 11:16:11 [post_content] =>
We know that Data Science helps in accurate, better and faster decision-making, similarly Tableau is an extremely powerful visualization software that helps to make more and better data-driven decisions. With Tableau you can easily learn to analyze and display data with a simple drag and drop design; it primarily comprehended in business intelligence and analysis. Let me make it more simple for you, Tablue is a BI tool used to visualize and analyse critical data in an easy and attractive format, which is currently being used by thousands of companies worldwide, even some business organization consider it as a 'must-have' for projects related to Data Science.
Well, before digging deep into the features of Tableau, let first understand what is Data science, how data visualization is being used in data science to solve problems, communicate predictions and make better business decisions! Data Science is basically about discovering knowledge, finding patterns and hidden insights from a large database. Data scientists transform this raw data into models and visually communicate these meaningful insights about a product or customer information using data visualization such as statistical graphs, plots, information graphs and other tools. In simple words, Data Visualization allows scientist to give the extracted data a visual form through visual representation using charts and non-charts. With data visualization, data findings become more communicable and complex data becomes more accessible, understandable and useful. It has even been advised by industry experts that if you are pursuing a career as a Data Scientist or Data Analyst, then Data Visualization is 'must-have' skillset!
I hope you got a fair idea on "how data visualization supports communication?" Now lets learn how Data Visualization with Tableau helps in making communication more clear, attractive and how it contributes to make more data-driven decisions! Well, Tableau's ease of use comes from its 'drag and drop interface' feature, that is, it lets users to perform the tasks like sorting, comparing and analyzing with more ease and comfort; to be more precise, its a hassel free software that is compatible with multiple sources, including excel, SQL server and cloud-based data repositories. Moreover, the simple representation of graphs is merely the tip of the iceberg, there is a wide array of visualization methods to present data in more effective, interactive and attractive ways, which are basically categorized into two types, that is 'General types of data visualization' and 'Specific methods to visualize data'.
The common general types of data visualization includes Chats, Tables, Graphs, Maps, Infographics and Dashboards, while the more specific examples of methods to visualize data are Area Chart, Bar Chart, Box and Whisker Plots, Bubble Cloud, Bullet Graph, Cartogram, Circle View, Dot Distribution Map, Gantt Chart, Heat Map, Highlight Table, Histogram, Matrix, Network, Polar Area, Radial Tree, Scatter Plot (2D or 3D), Streamgraph, Text Tables, Timeline, Treemap, Wedge Stack Graph, Word Cloud and Mix and Match method. We can even say that Data Visualization with Tableau makes an A-1 choice for Data Scientists and world-class software solution for business organizations.
Another feature of Tableau that makes a great tool for Data Scientist/Data Analyst is that it offers a seamless cross-language operations with Python, R and also with DBMS like SQL. This unique functionality of Tableau allows users to import the R and Python scripts in Tableau, that not only helps the user to access to a rich collection of statistical analysis with ease, but also let them gain a deeper insight from the data, and provides more accurate approach to predictive analysis. Well, you can even create visuals quickly with Tableau, and can switch between models to find the best representation chart that best represents your information with just few clicks, it can easily manage huge amount of data and allows customizing options along with hassel free integration with multiple data sourses. In simple words, Tableau is just more than a data visualization tool, it is more like a new approach the graphical representation of data that makes communication faster and data more attractive. It is fast, user-friendly and a simple-to-use tool, that helps to make more data-driven decisions.
Now, let see how the integration of R and Python with Tableau amplifies data with visual analytics? Well, Tableau makes it easier and quicker to identify patterns and build models by integrating with the programming language R and Python. With R, patterns can be analysed and even can be reproduced effortlessly, users can also create multiple charts to get meaningful insights, which increases the possibility to fetch the unseen patterns within the datasets. Furthermore, the data discovery is only with Tableau's in-built drill-down and data blending features. Moreover, with such extensive functionality in data exploration, every industry around the world wants to harness the power of Data visualization to stay ahead of the competition.
So if you are feeling intimidated to learn Data Visualization skill with Tableau, then check out the details related to our Tableu training program at our website and get certified in Tableau from either IBM, Microsoft or Harvard University.[post_title] => Data Visualization with Tableau [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => data-visualization-with-tableau [to_ping] => [pinged] => [post_modified] => 2019-04-26 11:16:13 [post_modified_gmt] => 2019-04-26 11:16:13 [post_content_filtered] => [post_parent] => 0 [guid] => http://edure.in/?p=229 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 216 [post_author] => 1 [post_date] => 2019-04-17 09:13:27 [post_date_gmt] => 2019-04-17 09:13:27 [post_content] =>
Do you know that each time you browse the internet, search at youtube, google some trends, shop online or even when you like a fb page or post, you are creating and sharing data about you; each time and in every single minute you are passing valuable info about your interest, preferences, and trends. Do want to know, how these information about you being used in this data-driven world? Well, all these raw data are extracted to find meaningful insights and patterns by Data Scientist/Analyst to help offline/online enterprises to figure out current trends, which help them to plan their future operational strategies and business development. In simple words, Data is transforming the digital world unexpectedly; be it offline or online enterprises, it is redefining the way of how we do business.
The accessibility of data has opened many possibilities towards development; not just the technological development but also for the business development. In short, data has the potential to turn the table around for any business! In the current scenario, each and every company around the world wants to incorporate data analysts into their company to make better and faster business decisions; be it a start-up, well-established companies or the top MNCs, everyone wants to take full advantage of the critical data around them to stay ahead of the industrial competition. Remember, it's just the beginning of this data driven world, there is much more to come and the potential is not explored to the fullest, the future is just about to unfold itself.
A research has pointed out that the data has started creating a massive impact on business, on our way of living and even how we connect with technology. In every single day around 2.5 quintillion bytes of data are created, which drives a rush among global companies to hire Data scientists to tame their business critical data, even the demand for a Data Scientist job has grown from 15% to 28% annually. Just like the more data is being produced, it will demand more number of analysts. Even Eric Schmidt of Alphabet Inc recently stated on the impact of data science on Industries that, "Not sure whether Data Science can forsee the future or be able to predict the world's end or not, but as for now it is literally escalating the growth of industry by 7% faster than any time in human history." The biggest opportunities of this digitally revolutionizing world is undoubtedly in Artificial Intelligence and Machine learning and Data is only paving the path for the AI revolution to come.[post_title] => Impact of Data Science on the Digital World [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => impact-of-data-science-on-the-digital-world [to_ping] => [pinged] => [post_modified] => 2019-04-17 09:29:40 [post_modified_gmt] => 2019-04-17 09:29:40 [post_content_filtered] => [post_parent] => 0 [guid] => http://edure.in/?p=216 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 207 [post_author] => 1 [post_date] => 2019-04-11 06:19:41 [post_date_gmt] => 2019-04-11 06:19:41 [post_content] =>
Eric Schmidt of Alphabet Inc recently stated on the impact of data science on Industries that, "Not sure whether Data Science can foresee the future or be able to predict the world's end or not, but as for now it is literally escalating the growth of industry by 7% faster than any time in human history." Thus, as being from an IT industry, we also share the same thoughts on the wide possibilities of data science. Hence it won't be too long when Data Science will become the next big thing in the near future! Well, here's why?
Although the field is new, yet it is proliferating its demand in the industry and expanding its career scope in the analytic field. Well, just like a flower can bloom only if it is a bud, similarly Data Science is an unseen field which is as new as a bud, and has many potential to unfold, to be explored! According to a report by Rutgers Online, which says that around 76% of Data Scientists have less than four years of working experience, which means that there is a shortage of skilled Data scientist globally. The report also points out that there is shortage of 79.7% data science professional around the world; countries like US alone need 1.5 millions of Data Scientist and Analyst to tame their large size unstructured business data. Well, the shortage of scientists and their lack of enough experience also states that the field is yet to be explored, it is yet to unlock its superpower literally!
Secondly, the career roles of the Data Science is yet need to be scrutinized. As per a survey report, only 55.9% scientist are working as a Data Researcher/Scientist and around 40.2% of professionals are working as a Business Developer Analyst. The fields like Data Architect, Data Administrator, Data/Analytics Manager, Business Intelligence Manager still remain mostly untouched. Although, Data Science has become the hottest job of the decade, yet it still remains mostly unexplored, unseen, unknown; in simple words 'Alien'.
Although, on one side it is yet to me be scooped out, yet has some percentage of explored fields, and one of them is 'Deep Learning with AI and ML'. It is being predicted that Deep Learning will be a significant tool kit for Data Scientist that will let them to foresee the developing future and scopes. Tech giants like Google, Netflix, Amazon and even researchers at MIT uses deep learning to predict future, that is, it assists them to figure out what their viewers or audience want to watch next or buy more. Where is cutting edge and uses neural networks to echo the human decision-making, there Deep learning goes much more deep, that is, with its advanced data feeding system, it can mimic humans' thought and intelligence. Well, it is only a glimpse of the power of Data Science, there is much more to come! Soon, the future will see the business leaders using the magnificent power of data science to unfold the business possibilities.
Behold, the future of next big thing is here![post_title] => What is the Next Big Thing in Data Science world? [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => what-is-the-next-big-thing-in-data-science-world [to_ping] => [pinged] => [post_modified] => 2019-04-11 06:19:43 [post_modified_gmt] => 2019-04-11 06:19:43 [post_content_filtered] => [post_parent] => 0 [guid] => http://edure.in/?p=207 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 191 [post_author] => 1 [post_date] => 2019-04-03 13:24:11 [post_date_gmt] => 2019-04-03 13:24:11 [post_content] =>
According to a recent survey, which states that about 58% of companies around the world have adopted the AI technologies into their various businesses to expertly manage their operational strategies and business development, where 12% of industries still sticks with the age-old computer systems for their business performance tracking, stock management and development. As being in the middle of an AI transforming era the survey result might have surprised many of us; it also makes us think 'why these businesses still remain unaffected by the digital revolution, where as the use of Artificial Intelligence can unlock many business potentials! Furthermore, it connects several other concerns by many small industrialists like 'Will AI perfectly fit into their business operations, how can an AI transform their business, how AI operation will affect their cyber security and so on'. So let's end your curiosity by giving you an insight on the various upgrade an AI can make when it is embodied into your business; be it small or big, an AI can grow your business wide with its intelligence!
AI is actively being adopted in the industries like Healthcare, Transportation, Manufacturing, Retail, Wholesale, Logistics, Education, Navigation, Agriculture and even also in Gaming. Moreover, companies like Amazon, Walmart, Target, TCS, IBS, Alibaba, IBM, Century Tech had already leveraged the magnificent power of AI to stay ahead of the curve. But still the only question that persist is 'how AI can bring your slow growing business into action?' Well, let's breakdown the departments where AI is actively incorporated to boost business process, production, performance and to achieve customer satisfaction:
1. Inventory management
It is difficult to keep a track of factors like inventory/stock levels, space optimization, stock movements, demand and supply of stocks, access daily sales report and moreover, it is hard to manage inventory in bulk. This where the new-gen technology steps in; AI will lend you a hand to manage your inventory effectively. With the pre-set algorithms in Artificial Intelligence you can automate the inventory management, which will eliminate the manual need for management. While your AI will be managing your inventory, you staff will be taking care of your customers. With AI change the way industrialists have operated their inventory so far. With AI in your business stop worrying about your stocks!
2. Automation and Logistics
p>It has not been too long since the arrival of Humanoid Robots, and they have already started walking among humans. The introduction of Automated technology in the workforce has escalated the activity and production process, especially in the automobile industries. These AI robots automate the production operations, inventory management and supply chain, which will enhance the efficiency of a company, while optimizing workforce, at the same time preserves energy and time. The predictive analysis of an Artificial Intelligence will revolutionize your industrial's stocking efficiency and business growth.
3. Business management
Artificial Intelligence is quickly being adopted in business management by industrialist for seamless business process. As we know around 2.5 quintillion bytes of data is being created in every min which is stored at the database. Have you wondered, why these data were collected, how will these data make an impact on your business? Well, the data is useless unless and until it is being processed and extracted to get meaningful insights or patterns. And when it comes to data mining it is almost impossible for humans to analyze a large size data. This is where Machine Learning and Deep Learning algorithms play its significant role in Business management; using AI algorithm analyst finds valuable insights which help in better decision-making. The retailers and other business professionals study these patterns to figure out customer's behavior, interest, habits, and even discover product trends. Thus, with AI predictions many companies like retailers plan their future marketing strategies to enhance their business process and performance.
Well, a product's production value and selling price makes a great impact on marketing and sales sectors. And this where AI is mostly used by an industrialist to manage their marketing strategies. The Artificial Intelligence studies the customer behavior and shopping pattern from the transformed data, based on which it figure out an attractive price optimization for one set of customers, while for another set of customers, it provides different combo offers on products, and as for retailers, AI will ensure the profitability with its logistics.
5. HR management
AI is revolutionizing the way companies manage their workforce, and now, every organization is looking for an HR automation; to increase productivity, reduce human effort and employment engagement in general. Infact, for MNC companies, recruiting as well as employee management itself need a large workforce, and for such companies AI HR solutions takes Human resource management to next level. This new-gen technology will not only assist you n seamless employee management, evaluating eligible candidates, workload management and employee recruitment, but also help you to scan, read and evaluate applicants quickly, save time by generating shortlists of qualified candidates based on the applicant’s profile and also handles the interview scheduling back-and-forth. Many industries, especially MNC companies, embodies AI HR management to make management smarter and work effortless.
6. Virtual assistance
Virtual assistance like AI Chatbots such as Natasha, Alexa, SIRI are some examples of AI application which build to boost customer satisfaction, happiness and experience in shopping. These customers oriented AI personals will assist customers in their shopping, direction and enquiries. With such assistance shopping becomes more approachable and customer-friendly!
7. Customer assistance
Walmart has developed a Facial recognition software, which will analyse customer's mood as soon as they enter the store. Such AI software analyse the mood and frustration level of a customer to define the level of satisfaction and dissatisfaction at the store. As soon as the AI figures out that the customer's dissatisfaction, it will assign a customer executive to address the customer's issues, so that they can revive their relationship with the store.
Stay ahead of the curve with AI optimization in Business; be it small or big AI can super-power your Business![post_title] => How Artificial Intelligence helps Brands grow? [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => how-artificial-intelligence-helps-brands-grow [to_ping] => [pinged] => [post_modified] => 2019-04-04 10:58:37 [post_modified_gmt] => 2019-04-04 10:58:37 [post_content_filtered] => [post_parent] => 0 [guid] => http://edure.in/?p=191 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 157 [post_author] => 1 [post_date] => 2019-03-21 06:40:27 [post_date_gmt] => 2019-03-21 06:40:27 [post_content] =>
Did you know why, the Data Scientist has become one of the most demanded, fastest-growing and highest paying career roles in the world! You might find this info useful that the shortage of skilled professionals in a world which is rapidly turning into a data oriented era, has led to the huge demand for Data Scientists in start-ups as well as in well-established companies globally. In every single day around 2.5 quintillion bytes of data are created, which drives a rush among global companies to hire Data scientists to tame their business critical data, which will help them to be ahead of their competition. Thus, the demand for Data Scientist jobs is projected to grow by 15% over the next five years, which translates to nearly 364,000 new job postings expected nationally by 2020. Even though the field is new, yet it is growing quickly and becomes one of the sexiest professions of the 21st century!
Now, let's review the career outlook for you in Data Science. As we know, Data has become a fundamental part of our everyday work. Moreover, the way AI is tremendously transforming the world around us, either everyone wants to be a Data Scientist or just every company wants to hire one! Data science and Analytics are now more than just a buzzwords, in the present scenario they are the essential tools of this AI driving world. Thus, opening a wide range of prominent job titles for you to choose, like Data Scientist, Data Architect, Data Administrator, Data Analyst, Business Analyst, Data/Analytics Manager and Business Intelligence Manager. Hence, with the millions of job openings around the world for Data Scientist, it has become the hottest job of the decade!
You might think that there might be a bright future for Data Science in the countries like US, but what's the possible career scope does India have for Data science! Then let me tell you that, India is only second to America in terms of recruiting data science professional. Moreover, the demand for data scientists is more likely only to escalate by the end of 2019. Even the demand for Data scientist and analysts are hiked by more than 50% over the last two decades, due to lack of skilled professional in Data science all over the world. Do you know that there are many analytics projects that get outsourced to India due to the shortfall of skilled hands. Even 17% of the companies in India are looking for freshers, whereas only 39% of analytics jobs are open for professionals, along with an amazing pay scale starting with 4-6 lakh per annum and it will only mean to increase with experience.
Based on a survey conducted by Analytics Mag India, we have listed out the top 10 leading organization with most numbers of Data Scientist/Analyst openings in India and world wide: Amazon, Citi, HCL, Goldman Sachs, IBM, JPMorgan Chase, Accenture, KPMG, E&Y & Capgemini. Well, in terms of Indian cities, Bengaluru accounts for the highest number of data science and analytics job opening, that is with 27%, followed by Delhi with 22% and Mumbai with 17%, while industries like retails, telecom, e-commerce, banking and financial sectors are also biggest contributors in the Data Science and Analytics job market.
The biggest opportunities of this revolutionizing world is undoubtedly in Artificial Intelligence and Machine learning, hence IT professions are looking forward to upgrade their knowledge, experience and skills in Data Science to secure the top roles. So learn that what earns you better![post_title] => What's the future of Data Science! [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => whats-the-future-of-data-science [to_ping] => [pinged] => [post_modified] => 2019-04-03 13:04:18 [post_modified_gmt] => 2019-04-03 13:04:18 [post_content_filtered] => [post_parent] => 0 [guid] => http://edure.in/?p=157 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 46 [post_author] => 1 [post_date] => 2019-03-11 12:01:47 [post_date_gmt] => 2019-03-11 12:01:47 [post_content] =>
We know how tricky battle it is to choose the apt programming language for your career framework in the Data Science and Machine Learning field! Well it will be no more a hassel for you, now that we will help you to make a better choice! There are quite many data science tools for programming available in the market, that serves the much-needed options to learn and work, but still there is a close combat going on, that narrowed down between the two popular languages- Python and R. And between the two, Python has emerging as the programming leader; used more in data science application.
Now, you mighty be wondering ‘Why is Python preferred over other data science tools?’ Let me make your dilemma easy for you by breaking down its features:
1. Simple to use and Easy to learn
The most enticing factor of Pyhton is that schooling its programming language is as simple as learning ABC; which draws the point to ‘easy and quick learning’. While comparing it with R and others languages, it offers a shorter learning curve. While also making a lead over other languages by promoting an easy-to-understand syntax. As well the simple use of the code, especially making it close resemblance to the English language, makes it better suited for beginners.
2. Portable, Extensible, Flexible and a Faster tool
When we say Python is the King of the programming languages, we aren’t kidding! Python has an abiding lead by emerging as a scalable language. It allows you to work faster and more flexible to solve problems and address the problems of specific nature, when compared to other languages like R. The portable and extensible properties of Python also allow you to perform cross-language operations seamlessly, by integrating programming platforms like Java, .Net, C and C++.
3. Choice of libraries
The variety of data science/data analytics libraries it offers serves as another significant factor that contributes to deep-rooting its leadership among other languages. Tensor Flow, Pandas, StatsModels, NumPy, SciPy and Scikit-Learn are some of the popular libraries in the data science community.
4. Python a tool for ML
As you know, Machine Learning is all about statistics, mathematical optimization and probability. Thus, Python has become the most prefered machine learning tool in the way it lets you ‘do math’ easily. It also offers a customization for neutral networks and deep learning with libraries like TensorFlow.
5. Graphics and Visualization
Another reason for the phenomenal rise of Python is that it actually comes with the option of varied visualization. The visualization packages help you to get a good sense of data, create charts, graphical plot and to create web-ready interactive plots.
The way Data science landscape is changing rapidly, the Python has emerged as the most apt data science tool to explore the basics of programming and let you expand your skills through scientific computing learning. Hope we have given you a clear picture of ‘Why you should learn Python over R!’ Master the basics of data science by choosing Python!
You might be wondering, why learn data science or why choose it as your career role? Let me make it simple for you, Data science is about finding and exploring patterns; you will discover some insight and pattern in the data, using that knowledge to solve the hard problems of the real-world and then, put in an effective way to communicate it to others. Data has become a fundamental part of our everyday work, whether it be in the form of valuable insights of the customers or information to guide products. Furthermore, it has transformed the way we work and communicate. Data science will let you make a massive impact on the world. If you are looking for an upgrade in your career, we will help you through our fast track course modules for Data Science training in Trivandrum.
Now, let me give you a deeper insight on ‘Why choose it as your profession?’ Did you know, the Data Scientist/Analysts has become one of the most demanded, fastest-growing and highest paying career roles in the world! And you might find this info interesting that in every single day around 2.5 quintillion bytes of data are created, which drive a rush among global companies to hire Data scientists to tame their business critical data, which will help them to be ahead of their competition. You may be also pleased to know that the demand for Data Scientist jobs is projected to grow by 15% over the next five years, which translates to nearly 364,000 new job postings expected nationally by 2020. Even though the field is new yet it is growing quickly and the demand is all time high; It has become one of the sexiest professions of the 21st century!
Now, let’s review the career outlook for you in Data Science. As we know, the shortage of skilled professionals in a world which is rapidly turning into a data oriented era, has led to the huge demand for Data Scientists in start-ups as well as in well-established companies globally. Moreover, the way AI is tremendously transforming the world around us, everyone wants to be a Data Scientist and every company wants to hire one! Data science and Analytics are no longer a buzzwords, now they are the essential tools of this AI driving world. Thus, opening a wide range of prominent job titles for you to choose, like Data Scientist, Data Architect, Data Administrator, Data Analyst, Business Analyst, Data/Analytics Manager and Business Intelligence Manager. Hence, with the millions of job openings around the world for Data Scientist, it has become the hottest job of the decade and we will help you to be the one, through our best Data science training in Trivandrum.
Now, after analysing all the bright sides in Data Science, you may find this field fascinating! The biggest opportunities of this revolutionizing world is undoubtedly in Artificial Intelligence and Machine learning, hence IT professions are looking forward to upgrade their knowledge, experience and skills in Data Science to secure the top roles. So learn that what earns you better! Thereupon see for yourself why choosing Data science is the most exciting career option!
We can help you plan your future brighter![post_title] => Why Choose A Career In Data Science! [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => why-choose-a-career-in-data-science [to_ping] => [pinged] => [post_modified] => 2019-04-04 13:37:24 [post_modified_gmt] => 2019-04-04 13:37:24 [post_content_filtered] => [post_parent] => 0 [guid] => http://localhost/edure/?p=43 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw )  => Array ( [ID] => 40 [post_author] => 1 [post_date] => 2019-03-11 11:53:40 [post_date_gmt] => 2019-03-11 11:53:40 [post_content] =>
Technology is revolutionizing and so are we! But have you ever wondered what’s with all the hike about getting into coding! And how leaning programming might impact your career! As we all know that Programming language is actually a way how we communicate with machines using codes in a specific format. But have this ever crossed your mind ‘ how vital it is to learn programming language to jumpstart your career in IT field?’ let me put it in a simple way, In this IT-literate world, we are all expected to be highly-skilled in technology and fluent in computer programming, as it is key to a successful career in this digital transforming era. Well, it is never too late to learn, so let help you to figure out which programming language to learn in 2019!
As we all know, Java is the most popular general-purpose programming language and it is everywhere, but do you know ‘why Java is preferred as one of the best programming language to learn’, well, it is due to its simple object-oriented language, great performance and platform independence feature of ‘Writing Once, Run Anywhere’. As being a multi-platform open source library, it has an ability to combine innovation with stability and have various libraries which make the Java’s development easier. Not only for web developers but also for beginners, it is the most favored language.
Swift is a high-level comprehensive purpose language generated by Apple in 2014. Even though, it is new to the programming world, yet it mounted as one of the most popularly used languages. So If you wish to get into iOS application development programs, then you should consider choosing Swift.
Even though Python is not considered as the first programming language by web developers, yet it is seen as a great first programming language when it comes to learning coding! The most amazing factor of python is that it offers easy-to-understand syntax, which makes it simple-to-use, quick-to-learn and eas-to-deploy when compared to other major programming languages. Even its portable and extensible properties let you to perform cross-language operations seamlessly, by integrating programming platforms like Java, .Net, C and C++. Python comes with a rich collection of libraries and has emerged as a scalable language.
4. R language
Being an open source and statistical language, R makes it simple to use for beginners. Just like python R can also perform cross-platform seamlessly on different operating systems, which makes it one of the most commonly used programming languages by enterprises. Even R also provides an excellent framework and build-in libraries. In this programming world R is also emerging as one of the leading programming language in statistics and data science. So, if you are passionate about becoming a Statistician, then there is no better programming language to learn than R.
While PHP is considered as another easy to use and simple to learn programming language for beginners. It is a general purpose scripting language, which is used to create dynamic web page content. It is also considered as one of the most popular language among web developers, due to its broad range of usage. Those who are looking for a profession as a backend developer should aim to learn PHP programming.
Technology will only continue to grow in this AI driven world. To make sure your career keeps up with that growth, we can help you through our fast-track programming courses we offer in Trivandrum.
Sign up to be future ready![post_title] => What To Code In 2019! [post_excerpt] => [post_status] => publish [comment_status] => open [ping_status] => open [post_password] => [post_name] => what-to-code-in-2019 [to_ping] => [pinged] => [post_modified] => 2019-03-21 05:39:04 [post_modified_gmt] => 2019-03-21 05:39:04 [post_content_filtered] => [post_parent] => 0 [guid] => http://localhost/edure/?p=40 [menu_order] => 0 [post_type] => post [post_mime_type] => [comment_count] => 0 [filter] => raw ) )