Sunil Ahuja
Analytics Training Institute. Learn Basic Statistics Concepts for Data Science. Courses offered by AnalytixLabs. Learn Basic Statistics Concepts for Data Science. How to Learn Data Science and What Skills to Master from Scratch? What is Big Data Engineering or Modern Data Engineering? Artificial Intelligence and Machine Learning (ML) Opt for this Applied AI course if you want skills to build your own Machine Learning & Neural Network powered applied AI applications!
Over last couple of years, the demand for Python professionals with AI and Machine Learning skills is highest among Analytics recruiters. Theoretical concepts of Artificial Intellegnce are not suffiencient to use it for practical applications and that is where Applied AI comes into the picture. Through this course you will learn various aspects of Data Science, Machine and Deep Learning which you need to apply, both conceptually and practically, to meet tangible business objectives. What is Data Science With Examples? Top Data Science Courses & Free Learning Resources 2020. What does a business analyst do? Their Roles & Responsibilities. Who is the Father Of Artificial Intelligence? How to Become A Data Scientist - Step By Step Guide. Why Should You Learn SQL in The Age of Python & R? Top 15 Real World Applications of Artificial Intelligence. Types of Clustering Algorithms in Machine Learning With Examples.
Analytics Courses- Blogs. Analytics Courses offers by Analytixlabs. Analytics Courses - Professional Online Courses. How to choose right Business Analyst course? Business Analyst vs Business Analytics – let us first clear the confusion!
The term “business analyst” invokes a lot of questions in people’s mind such as what exactly this field is, for whom is it suitable, what does a business analyst do and many more such questions make it difficult for a beginner to exactly pinpoint the definite definition of this field. However, the one thing that everyone seems to agree on is the importance and the ubiquity of this field.
The main reason that this field raises the inquisitiveness of students and professionals alike is the very nature of it which is unique on its own. This article aims to answer all such questions that might have come across anybody’s mind who has ever been curious about this field and seeking to pursue a career transforming Business Analyst Course. Business Analysis is an umbrella term and with this blog we intent to make you understand the intricate nuances of it and how to start your career as Business Analyst.
What is Data Analytics? Career Guide - Analytics Stages, Skills & Jobs. What is Data Analytics?
The most phenomenal aspect of the 21st century has been the explosion of the pace and quantity at which the data is being generated. So much so that 90% of the world’s total data has been generated in the last few years. The meteoric rise and spread of internet accompanied by the massive decrease in the storage cost of data which has fallen from $300,000 for a GB (gigabyte) in 1981 to $0.10 by 2010 speaks volumes of the data revolution.
The availability of huge amounts of data has led to a range of techniques that allow us to use this data for achieving numerous goals. These techniques of analyzing data in modern times is collectively called Data Analytics. Before the turn of the 21st century, the data was generated as a result of various operations however, this data was not necessarily put to use to create further products. Data Analyst vs Business Analyst - Which is for you? Roles, Skills & Salary. If this question is on your mind for some time, then you’ve come to the right place.
Facts show that data analytics have always been a part of our workforce, consistently analysing data and facts for companies. In smaller organizations, often the job titles of data analysts and business analysts are used interchangeably. This is mainly because both these analysts handle data (from a broader perspective). In large (or more mature) organizations, these roles are treated differently.
At times, the line of difference may be blurred but, in the end, the job environment and what each does with the data differs. Logistic Regression In R. One of the most important algorithms in the field of Data Science is Logistic Regression and is among the essential algorithms learned by the students of Data Science.
Models created using logistic regression serve a very important purpose in the world of data science as they manage the delicate balance of interpretability, stability, and accuracy in the model with great ease. By understanding the types of business problems, the role of statistical models, the meaning of generalized linear models, etc. logistic regression can be comprehended. This article aims to explain the logistic regression formula, its difference with linear regression as well as its implementation in statistical tools such as R in a simple, easy to comprehend language. Logistic Regression is better understood when it is pitted against its regression-based counterpart- Linear Regression. Top 10 Advantages & Disadvantages of Artificial Intelligence?
Artificial Intelligence (AI) does not belong to the future – it is happening now.
With the global AI software market surging by 154 percent year-on-year, this industry is predicted to be valued at 22.6 billion US dollars by 2025. Invented by John McCarthy in 1950, Artificial Intelligence is the ability of machines or computer programs to learn, think, and reason, much like a human brain. How to learn AI and Machine Learning by yourself? 101 of Artificial Intelligence (AI) - What to Know as a Beginner? The existence of AI has instilled the fear of dystopia in most of us.
But that’s just fiction, where we have seen AI making human-killing machines or becoming potential lovers. So, the obvious query here would be – What is AI in the current context? You can call AI, the secret recipe that renders a design, mimicking human operation. AI has become the pivotal lynchpin in today’s digitized transformation. Although the definition of AI has transformed over time, at its core it has always been about machines that can think like humans – plan, reason, learn, solve problems, represent knowledge, show motion, perception and be socially receptive. Several recognized breakthroughs in the field of AI can be seen in the field of quantum physics, financial world, computer technology et al.
What is Business Analytics? Different components, tools, skills and career. Top 20 (Interesting) Data Science Projects Ideas. Data science goes hand-in-hand with artificial intelligence and machine learning.
All of them feed off each other and are set to change the entire scenario of the service-related sector inside out. Data science projects are already underway and their implementation is prominent. The best way for data scientists to improve on the data science aspect is by constantly working on newer projects and ideas on the implementation. What is Image Segmentation or Segmentation in Image Processing? Image Processing or more specifically, Digital Image Processing is a process by which a digital image is processed using a set of algorithms.
It involves a simple level task like noise removal to common tasks like identifying objects, person, text etc., to more complicated tasks like image classifications, emotion detection, anomaly detection, segmentation etc. With the growth of Artificial Intelligence algorithms and its ecosystem, Digital Image Processing using the Neural Networks has become popular in recent times. It has a wide variety of application areas like security, banks, military, agriculture, law enforcement, manufacturing, medical etc. How to learn AI and Machine Learning by yourself? Data Analyst vs Business Analyst - Which is for you? Roles, Skills & Salary.
What is Data Analytics? Career Guide - Analytics Stages, Skills & Jobs. How to choose right Business Analyst course? Why Python for Data Science is Industry's Top Choice? Latest Trends. The phenomenal growth of the data science and its related applications across various industries is felt and observed in the last few years and in the year 2020, it continues to rise exponentially.
With more types of data that are being generated, especially the sensor and IoT based data, the world has seen a fresh surge of Machine Learning requirements in the industry. Among various survey conducted across the globe, in one such report, IBM has stated that the requirement of both Data Scientists and Data Engineers are going to grow by 39% in this year. The meteoric rise of data storage, data handling and Machine Learning has kept both big and small service providers and industry players pondering on the question of the choice of tools to meet and resolve such monumental requirements. They need a powerful tool and the same time, a versatile one to both meet the list of requirements and perform all the Herculean tasks with an admirable ease.
How Personal Data Protection Bill Has Raised The Demand For Business Analytics Courses? Data Science vs Machine Learning vs Artificial Intelligence with Example. In today’s world, it is easy to get lost in semantics and especially those who are new to the field of Data Analysis, it feels like you are bombarded with a never-ending tale of jargons. Among these jargons, the most commonly used and often confused are Data Science, Machine Learning and AI Deep Learning. As per the Experts.
Machine Learning Vs Data Mining Vs Pattern Recognition. Job roles, skills & how to pursue a career. The role of a data scientist or an AI (Artificial Intelligence) engineer has evolved over the last five years. So much so that, these roles have become synonymous with complex problem-solving skills. This is evident looking at Gartner’s prediction for AI job markets. Gartner has predicted 2020 as a pivotal year for AI as artificial intelligence will drive job openings.
The estimated numbers show that AI has the potential of driving 2.3 million jobs in 2020 alone. While all these reads rosy and quite a bit positive, the challenge is the skill gap. Reports state that in 2019, 97,000 data science job opportunities remained vacant because of the dearth of appropriate talent. Pre-requisites to learn Machine Learning or AI.
The two major fields of study that are considSered extremely important and are in demand in the 21st century are Machine Learning(ML) and Artificial Intelligence (AI). With the recent influx of data and the revolutionary progress in the computer hardware, the capabilities of the AI and ML driven technologies have tremendously increased. Such technologies now affect every sphere of human life. While the application of these technologies is for creating models for accomplishing tasks as simple as predicting a type of customer to as complex as identifying a potential threat through facial recognition, no matter what the model is, there is a good amount of study that goes into their development. The sheer capability of this technology is something that attracts a number of aspirants to learn it and eventually make a career out of it.
While a number of courses provide a good learning experience, there are certain pre-requisites that one must comply to successfully go through these courses. Statisticians, Mathematicians and Engineers are Part of HR: The Big Shift in HR is Here! IoT and Big Data; They Work in Tandem. IoT (Internet of Things) and Big Data are like two sides of the same coin. We constantly read about how we are living in an era of connected devices. Research and Advisory firm Gartner predicts over 9.7 billion devices to get connected by the time we touch 2020.
Analytics as Service On Demand. All data generated by cloud, IoT and other systems is mostly unstructured data for which big data analytics is utilized in big way. 5V disused above represent 5V paradigm for big data. Most of data generated by cloud and IoT system is unstructured in nature represented by big data system.Huge data generated by cloud computing infrastructure over a decade only way to understand this is Analytics. Cloud computing is characterized by 5V Huge Volume of data, Variety forms of data (images cloud, sound cloud, video site like youtube), velocity of data (like in social media fueling social media analytics) , value of data, . It’s easy to conclude Cloud computing is also fuelling demand for Analytics. Not recently Every cloud platform from Microsoft azure and Amazon released its ML machine learning services to recognize this need more and more analytics, data mining, machine learning API/services are being added to cloud platform.
What is the Importance of the Integration of Big Data and Data Science? Why Is Machine Learning Becoming an Essential Skill? It should be a rather easy question if we are aware of the advancements taking place in the field of artificial intelligence. 5 Tips to Improve Data Insight Strategy. Pre-requisites to pursue the course. 8 (Interesting) Machine Learning Projects For Beginners. Increasing Importance of ML and How to Use it to Your Advantage! Among the disruptive technologies, Machine Learning is an amazing innovation. It is the ability imparted on machines to learn and perform on the basis of data and over time such machines develop themselves without human intervention.
Python Skills can be Vital for a Successful Career in Data Science! Looking Beyond COVID-19: How AI & Data Science Jobs Will Change In More Digitised World. At the time of writing, the global economy is shooting downwards as the impact of COVID-19 spreads across the world. What is the Importance of the Integration of Big Data and Data Science? An Effective Marketing Analytics Model for Your Business. Marketing Analytics gathers data from across all marketing channels and consolidates it into a common marketing view. From this common view, you can extract analytical results that can provide invaluable assistance in driving your marketing efforts forward.
Best 5 Big Data Analytics Skills You Should Not Miss. What Does the Future Hold for Machine Learning? Is it a Better Career Option than Statistical Modelling? How Data Centre Works for Airline Industry. Just if we look at our own lives and see how every step we take is dependent on information, we can easily guess how much information or data, as we call it, may come into play in galactic affairs as are conducted by an airline industry.
It is not so easy a guess actually. The international airport of Dubai handles more than 200,000 passengers a day which amounts to 80 million per year. While this records the very zenith of the airline business, no major airports fall too far behind. Now if you consider merely the flight details and Ids of so many people you know that is more information than you will want to keep account for. And airlines have to deal with a double edged sword – they need to keep track of certain individuals for security reasons while they also have to comply with the regulations that protect personal data and individual information of the general customers. Storing it all yet making certain parts available Classification and back up. Data Science Can Be For Everyone. Skills For a Great Career- AI And ML.
Why Learning Python Helps? Using Python Is a Satisfying Experience for Coders. Why Has Python Become One of the Most Loved Programming Languages? Business Analytics Course In Bangalore. What Scopes Does Business Analytics Hold for You? Personal Data Protection(PDP) Bill Is Reason Behind The Rising Demand Of Business Analytics Courses. The ABC of Business Analytics. How to Choose The Best Algorithm for Your Applied AI & ML Solution. India: The Largest Potential Field for Applied Artificial Intelligence. What Makes a Career in Business Analytics Lucrative. The AI and Machine Learning Trends to Watch Out for in 2020. Analytics as Service On Demand. 5 Tips to Improve Data Insight Strategy. Predictive Analytics: One Technique for Various Industries. Data Visualization: Key Terms. Data Analytics Can Save Lives, and It Does. How to Minimize Dirty Data?
The Big Question of Big Data Schema. The Growing Elements of Hadoop Ecosystem. What is Google Cloud Dataflow? What is Applied AI? How Finance Teams need Deeper Machine Learning. Business Analytics : The Past and the Future. Business Analytics Certification Course. How Finance Teams need Deeper Machine Learning. Why Digital Transformation Does Not Ensure Success. Why Analytics Skills are Highly Sought After! The Best Machine Learning Tools: Python vs R vs SAS. How beneficial is a Big data certification course? Important tips for a career in Big data analytics:vTeki. Important tips for a career in Big data analytics:vTeki. Why should you invest on a business analytics course?
Key to success in data science. What is so fascinating about Artificial Intelligence? Why is there an increasing importance for Big data in India? How Extensively Does Google Use Python? Tools that keep you alive in the data science industry. Top Advantages of a Career in Analytics Why Data Analytics is One of The Most Promising Sectors Today! 5 Factors To Consider Before Investing In A Machine Learning Course. Why Should You Invest on a Business Analytics Course? What is Expected from a Business Analyst. Business Analytics Course, Certification, Training in Bangalore, Delhi, India.