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Dexlab Analytics Starts National Level Training On Data Analysis Using OpenAir package of R

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Dexlab Analytics Starts National Level Training On Data Analysis Using OpenAir package of R

From Saturday, 6th June 2020, a team of senior consultants at DexLab Analytics has been conducting a national level training for more than 40 participants who are research scholars, MPhil students and professors from colleges like IIT, CSIR, BHU and NIT, among others. This one of a kind, crowd-funded training is being conducted on “Environment Air pollution Data Analysis using OpenAir package of R”.

The training is a result of the lockdown wherein DexLab Analytics is working towards its upskilling initiatives for professionals and subject matter experts across India. The training is being conducted in DexLab Analytics’TraDigital format – real time, online, classroom styled, instructor-led training.

The attendees will be taking up these interactive classes from the safety and comfort of their homes. They will be getting assignments, learning material and recordings virtually.

The one-month-long training will be conducted in R Programming, Data Science and Machine Learning using R Programming from the perspective of Environmental Science. DexLab Analytics is conducting this training module in line with the tenets of ‘Atmanirbhar India’.

Data Science Machine Learning Certification

DexLab Analytics is a leading data science training institute in India with a vast array of state-of-the-art analytics courses, attracting a large number of students nationwide. It offers high-in-demand professional courses like Big Data, R Programming, Python, Machine Learning, Deep Learning, Data Science, Alteryx, SQL, Business Analytics, Credit Risk modeling, Tableau, Excel etc. to help young minds be data-efficient. It has its headquarters in Gurgaon, NCR.

 

For more information, click here – 

www.prlog.org/12825521-dexlab-analytics-starts-national-level-training-on-data-analysis-using.html

 


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Mr Debuka is Key Speaker at EIILM’s Webinar

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Mr Debuka is Key Speaker at EIILM’s Webinar

DexLab Analytics is proud to announce that its CMO, Vivek Debuka, was the Key Speaker at a webinar hosted by the Eastern Institute for Integrated Learning in Management (EIILM), Kolkata on “Changing Trend in Business in the Post COVID-19 World”.

The webinar was held on 30th May, 2020 from 5pm – 6pm. Students of the Eastern Institute for Integrated Learning in Management, the chairman and director of the EIILM Dr R P Banerjee said, were excited and eager to attend the webinar, especially because the topic was an emerging one and relevant to their corporate career goals.

On May 27, EIILM posted a Facebook post that read – “EIILM’s initiative for enriching young minds with post COVID-19 business trends!!!! The Covid era has brought about a lot of uncertainties that have resulted in a new thought process in the ever-changing world of business. To orient our budding managers with the dynamic business trends, EIILM – KOLKATA Family has scheduled a Webinar on 30 May 2020, from 5-6 pm under the title “Changing Trend in Business in the Post Covid 19 World”.

Data Science Machine Learning Certification

DexLab Analytics is a leading data science training institute in India with a vast array of state-of-the-art analytics courses, attracting a large number of students nationwide. It offers high-in-demand professional courses like Big Data, R Programming, Python, Machine Learning, Deep Learning, Data Science, Alteryx, SQL, Business Analytics, Credit Risk modeling, Tableau, Excel etc. to help young minds be data-efficient. It has its headquarters in Gurgaon, NCR.

 
For more information click on the link here – www.prlog.org/12824488-dexlab-analytics-cmo-was-key-speaker-at-eiilm-webinar.html
 


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93% Indian Professionals Benefitting From E-Learning During Lockdown: Linkedin

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93% Indian Professionals Benefitting From E-Learning During Lockdown: Linkedin

The Covid-19 pandemic has struck India like it has scores of countries across the world. As of May 27, over 1,51,000 Indians have been tested positive for the novel virus and over 4000 people have died due to the contagious disease. India has been under lockdown for over two months now in an attempt at abating the spread of the virus due to movement and contact.


 

With all offices closed and work from home decreed across numerous sectors of the economy, professionals have been forced to adapt to a new mode of work and training. With more time on hand since they are working from home, professionals are upgrading their skills by taking up online training modules and classes. A recent LinkedIn survey throws light on this phenomenon.

LinkedIn’s Work Force Confidence Index

India’s foremost social networking site that helps individuals network with professional peers and find jobs and appointments has conducted a survey called Work Force Confidence Index. As per the survey conducted between April 27 and May 3, “India’s professionals are logging learning hours for not just knowledge acquisition but also to increase productivity. About half of respondents from mid-market firms joined courses that help them manage time better, improve prioritisation or stay organised”.

93% Indian Professionals Benefitting From E-Learning During Lockdown: Linkedin

93% respondents to upskill online in next two weeks

According to LinkedIn News India, 1040 professionals were surveyed by LinkedIn and 93% of them said “their time spent on e-learning will either increase or remain the same over the next two weeks”. Moreover, 60% of the respondents of which 74% were from the engineering domain said e-learning was a conduit to furthering industry knowledge. “Advancing in one’s career was a driver for 57% of all respondents and 3 in 10 active job seekers undertook e-learning to make a career pivot,” said LinkedIn News India.

What respondents learnt

Of the respondents, 45% said they hoped to learn to collaborate with peers through online learning in lockdown. Also, 43% said they wished to learn to manage time and prioritise and stay organised. Moreover, 40% said they hoped to learn something unrelated to work through online platforms. Becoming a leader and managing personal finances were pegged at 37% and 32% respectively by the study as goals and 24% said e-learning could actually lead to a change in career paths for them.

Advantages of e-learning

Travelling to work and back is taxing and time consuming. When you are working from home, you save on energy and time that can be used for something productive like e-learning training modules. They are easy on the pocket, accessible from absolutely anywhere you are and convenient to absorb and retain information and new things learnt. Moreover, there is a large online community to help you out with study material and guidance.

Data Science Machine Learning Certification

There are many popular e-learning courses in India, especially those around data science and artificial intelligence. DexLab Analytics is a premier credit risk modeling training institute that also trains professionals in artificial intelligence, machine learning and data science. This article was brought to you by DexLab Analytics.

 


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The Data Science Life Cycle

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The Data Science Life Cycle

Data Science has undergone a tremendous change since the 1990s when the term was first coined. With data as its pivotal element, we need to ask valid questions like why we need data and what we can do with the data in hand.

The Data Scientist is supposed to ask these questions to determine how data can be useful in today’s world of change and flux. The steps taken to determine the outcome of processes applied to data is known as Data Science project lifecycle. These steps are enumerated here.

  • Business Understanding

Business Understanding is a key player in the success of any data science project. Despite the prevalence of technology in today’s scenario it can safely be said that the “success of any project depends on the quality of questions asked of the dataset.”One has to properly understand the business model he is working under to be able to effectively work on the obtained data.

  • Data Collection

Data is the raison detre of data science. It is the pivot on which data science functions. Data can be collected from numerous sources – logs from webservers, data from online repositories, data from databases, social media data, data in excel sheet format. Data is everywhere. If the right questions are asked of data in the first step of a project life cycle, then data collection will follow naturally.

  • Data Preparation

The available Data set might not be in the desired format and suitable enough to perform analysis upon readily. So the data set will have to be cleaned or scrubbed so to say before it can be analyzed. It will have to be structured in a format that can be analyzed scientifically. This process is also known as Data cleaning or data wrangling. As the case might be, data can be obtained from various sources but it will need to be combined so it can be analyzed.

For this, data structuring is required. Also, there might me some elements missing in the data set in which case model building becomes a problem. There are various methods to conduct missing value and duplicate value treatment.

“Exploratory Data Analysis (EDA) plays an important role at this stage as summarization of clean data helps in identifying the structure, outliers, anomalies and patterns in the data.

These insights could help in building the model.”

  • Data Modelling

This stage is the most, we can say, magical of all. But ensure you have thoroughly gone through the previous processes before you begin building your model. “Feature selection is one of the first things that you would like to do in this stage. Not all features might be essential for making the predictions. What needs to be done here is to reduce the dimensionality of the dataset. It should be done such that features contributing to the prediction results should be selected.”

“Based on the business problem models could be selected. It is essential to identify what is the task, is it a classification problem, regression or prediction problem, time series forecasting or a clustering problem.” Once problem type is sorted out the model can be implemented.

“After the modelling process, model performance measurement is required. For this precision, recall, F1-score for classification problem could be used. For regression problem R2, MAPE (Moving Average Percentage Error) or RMSE (Root Mean Square Error) could be used.”The model should be a robust one and not an overfitted model that will not be accurate.

Data Science Machine Learning Certification

  • Interpreting Data

This is the last and most important step of any Data Science project. Execution of this step should be as good and robust as to produce what a layman can understand in terms of the outcome of the project.“The predictive power of the model lies in its ability to generalise.” 

 


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The link between AI, ML and Data Science

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The link between AI, ML and Data Science

The fields of Artificial Intelligence, Machine Learning and Data Science cover a vast area of study and they should not be confused with each other. They are distinct branches of computational sciences and technologies.

Artificial Intelligence

Artificial intelligence is an area of computer science wherein the computer systems are built such that they can perform tasks with the same agility as that done through human intelligence. These tasks range from speech recognition to image recognition and decision making systems among others.

This intelligence in computer systems is developed by human beings using technologies like Natural Processing Language (NLP) or computer vision among others. Data forms an important part of AI systems. Big Data, vast stashes of data generated for computer systems to analyze and study to find patterns in is imperative to Artificial Intelligence. 

Machine learning

Machine learning is a subset of artificial intelligence. Machine learning is used to predict future courses of action based on historical data. It is the computer system’s ability to learn from its environment and improve on its findings.

For instance, if you have marked an email as spam once, the computer system will automatically learn to mark as spam all future emails from that particular address. To construct these algorithms developers need large amounts of data. The larger the data sets, the better the predictions. A subset of Machine Learning is Deep Learning, modeled after the neural networks of the human brain.

Data Science Machine Learning Certification

Data Science:

Data science is a field wherein data scientists derive valuable and actionable insights from large volumes of data. The science is based on tools developed with the knowledge of various subjects like mathematics, computer programming, statistical modeling and machine learning.

The insights derived by data scientists help companies and business organizations grow their business. Data science involves analysis of data and modelling of data among other techniques like data extraction, data exploration, data preparation and data visualization. As data volumes grow more and more vast, the scope of data science is also growing each passing day, data that needs to be analyzed to grow business.

Data Science, Machine Learning and Artificial Intelligence

Data Science, Artificial Intelligence and Machine Learning are all related in that they all rely on data. To process data for Machine Learning and Artificial Intelligence, you need a data scientist to cull out relevant information and process it before feeding it to predictive models used for Machine Learning. Machine Learning is the subset of Artificial Intelligence – which relies on computers understanding data, learning from it and making decisions based on their findings of patterns (virtually impossible for the human eye to detect manually) in data sets. Machine Learning is the link between Data Science and Artificial Intelligence. Artificial Intelligence uses Machine Learning to help Data Science get solutions to specific problems.

The three technological fields are thus, closely linked to each other. For more on this, do not forget to check-out the artificial intelligence certification in Delhi NCR from DexLab Analytics.


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Netflix develops in own data science management tool and open sources it

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Netflix develops in own data science management tool and open sources it

Netflix in December last year introduced its own python framework called Metaflow. It was developed to apply to data science with a vision to make scalability a seamless proposition. Metaflow’s biggest strength is that it makes running the pipeline (constructed as a series of steps in a graph) easily movable from a stationary machine to cloud platforms (currently only the Amazon Web Services (AWS)).

What does Metaflow really do? Well, it primarily “provides a layer of abstraction” on computing resources. What it translates to is the fact that a programmer can concentrate on writing/working code while Metaflow will handle the aspect which ensures the code runs on machines.

Metaflow manages and oversees Python data science projects addressing the entire data science workflow (from prototype to model deployment), works with various machine learning libraries and amalgamates with AWS.

Machine learning and data science projects require systems to follow and track the trajectory and development of the code, data, and models. Doing this task manually is prone to mistakes and errors. Moreover, source code management tools like Git are not at all well-suited to doing these tasks.

Metaflow provides Python Application Programming Interfaces (APIs) to the entire stack of technologies in a data science workflow, from access to the data, versioning, model training, scheduling, and model deployment, says a report.

Netflix built Metaflow to provide its own data scientists and developers with “a unified API to the infrastructure stack that is required to execute data science projects, from prototype to production,” and to “focus on the widest variety of ML use cases, many of which are small or medium-sized, which many companies face on a day to day basis”, Metaflow’s introductory documentation says.

Data Science Machine Learning Certification

Metaflow is not biased. It does not favor any one machine learning framework or data science library over another. The video-streaming giant deploys machine learning across all aspects of its business, from screenplay analysis, to optimizing production schedules and pricing. It is bent on using Python to the best limits the programming language can stretch. For the best Data Science Courses in Gurgaon or Python training institute in Delhi, you can check out the Dexlab Analytics courses online.

 

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Artificial Intelligence Jobs: Data Science and Beyond!

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Artificial Intelligence Jobs: Data Science and Beyond!

Artificial Intelligence is the latest technology that the industry of computer science has been working on for quite some time now. Though it has not yet been possible to materialize the high-end AIs, weak/narrow Artificial Intelligence which includes, Siri, Cortana, Bixby, Tesla, are the ones that have grown to be simply inseparable in our daily lives. This is simultaneous with the widespread of the Artificial intelligence Course in Delhi, which is encouraging more and more students to explore new-age technologies. 

With the extensive research and tests carried out on all these new technologies to implement them in the modern industries; AI is yielding more jobs than ever before.

Jobs Springing from the Artificial Intelligence

Artificial intelligence and data always go hand in hand because it is the data that helps us gain insight into the results. Thus, it is not surprising that the professionals utter AI and data at the same instant.

When Amazon mentioned of up-skilling 100,000 employees from the United States to make them ready for the technology of the age, they also claimed that the machines with the ability to deal with data are responsible for most of these jobs.

There have been huge changes in the figures since then, with the data mapping scientists increased to 832%, the total data scientists jumped by 505%, and the total business analysts hiked about 160%. Besides, there is also a marked demand for the other employees, who are from a non-technological background. However, most of these are associated with Artificial Intelligence, like logistics coordinator and executive; process improvement manager; transportation specialist and so on.

Thus, in contradiction to our surmises that AI and its likes will throttle our jobs and crumble every other our opportunities of the same are turning out to be false for good!

Data Science Machine Learning Certification

Drawing to a Close

Whether it is Machine Learning, Data Science or Artificial Intelligence, we are noticing a rapid progress and can easily count on a better future rich with technology. However, with the increasing hardware, software and advanced computing, the need to grasp the pacing technology thoroughly is becoming predominant. Thus, Machine Learning Using Python, Neural Network Machine Learning Python and Data Science Courses in Gurgaon are rising in demand to meet the need of the mass. However, you should always go for the best Artificial Intelligence Training Institute in Gurgaon to imbibe a wholesome knowledge of the subject.

 


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Want to Grow Quickly as a Data Scientist? Check Out 6 Ways

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Want to Grow Quickly as a Data Scientist? Check Out 6 Ways

With the raging popularity of Data Science, only a few would be as unambitious as not choosing it as their field of work. Not only does Data Science open up a path long and promising for learning and attaining mastery but it also lets you get into the spotlight quicker than ever.

Most importantly, with the rising trend of Data Science, you can also shoot your career up.

Opting for Data Science, you can either be an employee in any of the distinguished IT sectors or you might also serve as a trainer, with your name all over the community.

But, as with all the other trades, marketing is important even when you seek for grounding your career in Data Science. But don’t worry because here we will give you some hacks to market yourself as a Data Scientist and grow as fast as feasible.

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Knowing the Inside Out of the Domain

Ensure that you have a deep knowledge of Data Science before starting to market yourself as a Data Scientist. This is because as more and more people are getting trained in Data Science and starting to pave their career in the same field, none but they with a steadfast knowledge would thrive. Furthermore, in this digital career, you shall also pledge to be always updated and Data Science Courses in Gurgaon can give you the edge.

So, it would prove to be indispensable if you invest a considerable amount of time to learn, on hands-on-experience, leading to chiselling your knowledge and skillset.

Delve into Social Media

When it comes to marketing, you shall never disregard Social Media. In fact, that is the platform which you must first target. Facebook, Twitter and LinkedIn is the trio that you must first address.

Navigate to your Social Media accounts as frequently as you can. There, try to make friends with the people of the same profession, interact with them, discuss various problems and highlight your feats.

Value your Content

As in marketing, the common phrase goes “Content is King”, the validity of this saying is never to be tested.

Like your friends from Media, Content Marketing and Digital Marketing, there is no alternative to create your content and build your own trust.

Note – Bad content and plagiarism are a strict no-no.

Speak Often

Data Science is a relatively new stream, meetings, conferences, discussions are happening almost all the time around the world. Hence, keep yourself aware of these events and try to participate in them both as a speaker as well as a diligent and inquisitive audience.

Grow this habit and you will be amazed at assessing the popularity of yourself incredibly fast.

Be Inclined to Help

Knowledge is always ought to be shared. If you discover that you have an irrefutable knowledge of something and someone is asking for help in your domain of expertise, then extend your helping hands to them. This way you will simply be recognised all the way more.

Deep Learning and AI using Python

Hackathons

For computer geeks and coders, Hackathons speak volumes. You should also try and participate in more such hackathons which are widely occurring. This will not only help you test your knowledge and understanding but will push you further and even help you extend the contacts in your professional field.

The points that we have highlighted here should surely help you be more marketable as a Data Scientist. So, keep these in mind and watch your career take a flight!

 

Interested in a career in Data Analyst?

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To learn more about Data Analyst with R Course – Enrol Now.
To learn more about Big Data Course – Enrol Now.

To learn more about Machine Learning Using Python and Spark – Enrol Now.
To learn more about Data Analyst with SAS Course – Enrol Now.
To learn more about Data Analyst with Apache Spark Course – Enrol Now.
To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

Python is the Leader in Data Science: Know Why

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Python is the Leader in Data Science: Know Why

From being simple and effective to being updated and thereby, solving almost everything that the booming industry of Data Science of today can look up to, Python boasts of it all.

It’s not a shock that Python is finding its uses in an array of industries. It is, in fact, the language that the Data Scientists rely on. Thus, our tailored courses of Python Certification Training in Delhi would be helpful for all in this digital age.

Let’s see some more of the advantages for which Python stands distinguished among the other programming languages:

Handling Data without a Hassle

The field of Data Science is entrusted with the handling of incredibly large amounts of data which is found to be intricate to compute. However, with Python, it is now simpler than ever. Any of the other high-level programming languages would make it rather difficult and messy compared to the peerless Python, if we talk about analytical and quantitative computing.

Open Source Programming Language

Python is an open-source programming language. Wonder why this programming language is the most preferred still?

It truly opens a whole lot of opportunities that the language can build upon, being open-source in nature. Furthermore, there is not a single restriction regarding Python. Thus, you can be as creative as you wish on this programming language.

It is Powerful and Easy to Use

Python is an easy language right from the start for which it has become so popular. Any of the beginners with just the rudimentary knowledge can start fine with Python. Besides, once you are on with this programming language, you can start progressing with it day by day at your own pace.

The implementation of the code has a slower approach in the languages: Java, C and C#, but if you try Python, you would discover that it is fast to debug and effective to perform. The prompt results in coding would aid with an added boost in your work.

In the Library of Python

Python is an all-absorbing language that even supports the cutting edge technologies of Machine Learning and Artificial Intelligence. And on top of it, Python also offers its users a colossal database of libraries. Therefore, you can simply check in the libraries, import them and then implement all of them in your day to day coding.

It is Highly Scalable

In the parameter of scalability, Python superbly stands out. The programming languages: R and Java certainly falls short in this factor. Thus, with the ease of scalability and quicker turnaround times, data scientists and nearly all of the organisations exploring Data Science, are choosing Python over any other existing languages.

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It is Peerless in Visualisation and Graphics

As the smooth rendering of quality graphics and visualisation is the demand of the age, Python fits in quite comfortably here. With an exhaustive range of options for visualisation, which are simple and efficient, the world of Data Science is rooting for Python.

With all the benefits that you can reap, Python for data analysis is a must, if you want to be absorbed in the industry of Data Science.


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