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Category: Analytics

Is Machine Learning Right for You?

Posted on by Imarticus Learning

The world today has been technologically changed by machine learning and big data analytics. Our challenges today, lie in understanding the large volumes of data we have created and using it intelligently. 

That is precisely what Machine Learning, Artificial Intelligence and machine learning courses in India have helped us with.Examples are everywhere and especially on your smartphone. ML has helped understand your shopping preferences and auto-suggests what you could be interested in. The same thing happens when you use your Facebook account which tags your friends and suggests videos that may interest you.

The Data Analyst and ML Engineer Roles
As a Data Analyst, your end goal is to use data to produce insights that are actionable by other humans. The ML Engineer does the same. However, its end goal is used by artificial intelligence systems to make the machines or systems behave in a particular way. This decision will impact the service or product and eventually the success of the enterprise.

Skills Required
ML requires a mix of skills to understand the complete environment, the how and the why of the issues you are designing and dealing with. Machine learning courses should ideally cover

Computer Science and Programming
Fundamentals including data structures, algorithms with their functioning, complex and complete solutions, approximation in algorithms, and system architecture. Hackathons, competitions in coding and plenty of practice are best at honing skills.

Statistics and Probability
The engine for ML runs on these and helps it in validating and building models from the provided algorithm which evolves from statistical models.

Evaluation and Data Modeling
These are important as ML build the model based on measures, weights, models, iterative algorithms and strategies it develops depending on its learning from the base algorithm.

Applying Libraries and ML Algorithms
Libraries and APIs like Theano, Scikit-learn, Tensor Flow etc., need a precise model and effective application for success.

Software Engineering and System Design
Output depends on the software and its design for applicability to provide robust, scalable and efficient solutions.

Job Roles with Demand
Data analysts, core ML engineers, applied ML engineers, and ML software engineers are jobs that will exponentially rise. Skills and Big data Hadoop training courses that help in applying ML algorithms and libraries will stand you in good stead. System design and software related jobs using ML, data modeling and evaluation, ML probability and statistics experts, and CS fundamentals and programming specialists jobs offer huge potential for professional development in the near future.

The Future of Machine Learning
Machine Learning, data analytics, AI and predictive analysis has no limits to its applicability and has already impacted every field like health, computers, life sciences, banking, education, insurance, finance, and literally every field you can think of.

Your weather forecasts, prices on stock exchanges, trends for the next decade, oil exploration, the MRI machines, predicting the subsequent breakdown, strategy building for marketing, automatic machine lines, and production are all today complex uses of techniques of using machine learning and AI for data analysis, analytics and predictive analysis. Will there be any field that is not impacted then by ML in the future?

If ML interests you then now is the time to update your knowledge and upgrade your skill-sets. There are courses and materials readily available. However, you will need a plan of action that you must adhere to. Good Luck!

Importance of Data Analysis and why you should learn it?

Posted on by Imarticus Learning

Inspection,cleansing, transformation and modelling of data in order to achieve information that further suggests conclusions and assists with decision making is what data analysis is all about. It’s a rapidly booming field of study for the youth, and companies are always on the hunt to find people who are masters at this procedure so as to increase their growth.

Analytical and logical tools are used to determine and accurately learn data analysis. These skills need to be learnt and honed over time in order to land yourself a good position in this field.              

Analyzing data is important for any business, old or new. It provides a clear understanding of customer behavior and much more essential business intelligence to promote growth and rectify mistakes if any. The first step in this huge process is defining an objective, without which the purpose of the study is lost.

Posing questions is the next step, after which comes data collection through various online and offline tools and techniques. This is the most crucial part of the process, as you need to define your objectives to learn data analysis as accurately as possible.

Learn data analysis by learning the essential tools and the most basic ones used in this line of work. One of the most widely used programs for data analysis is Excel. The other ones are Python, SQL & R. It is easy to get defocused with so many programming languages available and not knowing which one to learn first.A road map always helps while learning something new. R is a good place to start in terms of programming language. R Studio is an essential program to have to learn data analysis.   

If you want to learn data analysis, do not get intimidated by the courses available. You can look up educational websites and just by investing a few bucks, and you can know all there is to it. The most important part to remember before starting is having a fair idea of which software or program does what. It is always better to practice till you’re perfect, rather than spend time only on reading about it. There are also a lot of offline courses available to keen learners in order to learn data analysis.

If you’re sure about pursuing this field, then investing in a good college, institute, or course can help bring out the best in you. While there are many crash courses for the same, not many degree courses are available to learn data analysis. Interning under data analysts in your city of choice and your company of choice will also contribute largely towards technical and practical knowledge. Companies generally welcome promising interns and are willing to work towards their progress as a professional while seeking a fresh approach to business from them in return.        

The best way to excel in this line of work is choosing a specific skill you want to take forward professionally. It is the best bet for making the most of there sources available to you to learn data analysis.             

We offer data analytics courses at our centers in Mumbai, Thane, Pune, Ahmedabad, Jaipur, Delhi, Gurgaon, Bangalore, Chennai, Hyderabad, Coimbatore.                                     

Top tips on how to apply data analytics in your project

Posted on by Imarticus Learning

Data science and analytics are two extremely useful tools that can give accuracy to your project and help automate repetitive tasks. With the demand and scope of data analytics growing with each passing day, companies are trying to integrate everything and get as much information on it as they can.

Data science techniques and analysis are quite helpful because they can be used to enhance the decision-making capacity of your manager, predict future revenues, understand market segments, and produce better content. In the healthcare sector, this technology can be used to diagnose patients correctly.

But how do you integrate data analytics into your professional projects? For that, a sound knowledge of the same is required. Even if you learn the basics of data analytics, it will give a major boost to your career. The entire world is moving towards digitization, and so data analytics is required to gather, analyse, and make sense of the data in front of you.

In order to become an expert in data analytics, and incorporate it seamlessly into your project, you need to have a data analytics training.There are many data analytics courses that you can take for a better understanding of data science and analysis. Here is a list of some of the best data analytics courses available online.

  • Introduction to Data Science

This data analytics training course requires a basic understanding of R programming language and provides an in-depth insight into the necessary tools and concepts used in the data science industry. They also work with powerful techniques for analyzing data and use real-world examples to help you gain clarity over the concepts.

  • Applied Data Science with Python

It is being offered by the University of Michigan. It aims to introduce learners to the specialized version of data science through Python. It is for learners with an understanding of Python, and want to expand their knowledge by incorporating the essentials of statistical,machine learning, information visualization, text analysis, and social network analysis techniques into their projects.

  • The Python Mega Course: Build 10 Real World Applications

This data analytics training is aimed at people with no background of Python, but are interested in learning basic as well as advanced skills of Python and data analysis. It is for people with no previous or little programming experience.

It does not rely on a lot of theoretical teaching but focuses instead on giving problems to the students that they can solve by doing. This course uses video, quizzes, real-world examples to familiarize learners with Python in the beginning and then enhance their skills later.

  • Social Media Data Analytics

This is one of the best data analytics courses available online that especially caters to social media. It is for people who want to use their data analysis skills to get the best out of social media.This course involves giving assignments and mini-projects, which would require you to use your data analytics skills to leverage your social media presence.

How to Work on Deep Learning programming?

Posted on by Imarticus Learning

Learning Algorithms

Algorithms are at work all around us. Right from suggestions displayed in a text box while using Whats App to time boxing traffic signals, algorithms greatly improve the quality of human life these days. The more efficient the algorithm, the better the quality of service. Imagine an elevator system for a skyscraper with a thousand floors.

An adaptive machine learning algorithm can change the way it works depending on the demand and timetable of people going to different floors and dramatically reduce the waiting time for a person taking the elevator when compared to a static algorithm with no feedback loop.

Machine Learning is nothing but the improvement in performing a task with experience.The more the experience, the better is the performance of a machine learning algorithm. It can also be used for predicting the outcome of an event based on the historical data available. Filtering spam from your mailbox, Commute time predictions, Suggestions in social media, digital assistants are a few examples of the applications of machine learning algorithms.

Deep Learning and the Complexities involved

The fundamental rule in computer science is the use of abstractions. All concepts act as building blocks to another seemingly advanced concept, which is nothing but a layer of abstraction added over the older concept.

Algorithms, data structures, machine learning, data mining are the building blocks of Deep learning which is Machine learning and the concept of feature wise classification. Deep learning defines which feature characterizes a pattern and then uses data mining to classify, compare and define a feature.

Deep learning algorithms typically take more time to train but are more accurate and dependable as experience increases. They are used for speech recognition. NLP. Computer vision, Weather pattern analysis etc. They are usually implemented using neural networks. Deep learning is a subset of machine learning.

How to Learn Deep Learning programming

Below are few ways to understand and work on Deep learning:

  1. There are several machine learning courses, and deep learning courses available online,mostly in Python and R. Python training is usually a prerequisite for these courses. Some of the best ones are available in Udemy, Course Era, edX etc. These courses can be completed online and are prepared by the best minds in the field.  

  2. Understanding the inbuilt Python libraries: The future of machine learning and deep learning depends greatly on the inbuilt library support python provides. Tensor Flow, Thea nos, Pandas etc. are a few powerful libraries which it provides for programmers to explore deep learning concepts.

  3. Knowledge of Machine Learning or doing a machine learning course is generally preferred before diving into deep learning because conceptually machine learning is a general form of learning compared to the more specific deep learning. But based on the programmers understanding of the basic concepts, exposure to Python and R libraries, deep learning can also be started directly.

  4. However, the classic order is, do a python course -> Do a machine learning course -> Do a deep learning course and then contribute to the deep learning community after practice and execution.

  5. All the tools involved are opensource, so with sufficient interest, programming expertise and Python knowledge, cracking Deep Learning should be an easy task. Take part in the community and practice, practice, and practice to excel.

All the very best for your journey into Deep Learning..!!

Can Artificial Intelligence be self-aware?

Posted on by Imarticus Learning

Artificial Intelligence has gradually been spreading its wings to more and more sectors wherein only humans could work until now. A prime example of this is the introduction of an artificial intelligence process to vehicles, making self-driving cars a reality.

While this is a significant development, it pales in comparison to the possibilities that could be unlocked if we have a computer that is completely aware of itself and its surroundings. These machines could be sent to do a variety of jobs that humans find difficult.

In fact, it could reach such a point wherein robots replace humans at every job, leaving humans to live their lives in lazy bliss. This could completely shake up society as we know it and leave humans without a sense of purpose. This also raises the question of legality when it comes to robots. Would be held under the same accountability as humans, or scarily still, would they band together and eliminate humans altogether?

There are varying views among researchers about what consciousness is and whether machines could someday achieve it. Some researchers say that consciousness develops with constantly accepting new information, retrieving the old and processing all of it into thoughts and, subsequently actions. If this assumption is true, then any consciousness developed by computers will be the most advanced one, even more so than human consciousness.

They will be able to access millennia worth of information within a fraction of a second and be able to make decisions which are both more complex and more logical than what any person could accomplish. However, some researchers disagree with this opinion,saying that some factors that contribute to consciousness, such as creativity and compassion, are not the result of calculations and will always be exclusive to humans.

Another view of this topic is the quantum view, which takes into account the quantum theory of physics. According to this view, all the physical aspects of this world and consciousness complement each other all the time. It goes on to say that whenever a person observes or manipulates any physical object, noticeable change could be observed due to that person’s conscious interaction with the object.

This can be explained by considering consciousness as something that exists by itself and isn’t derived through physics, merely needing a medium such as a brain to manifest itself. If this is true, it seems highly unlikely that machines would be able to tap into this consciousness.

Another factor to talk about here is computational programming, which is the basis on which every computer on the planet runs. For a computer to be self-aware, it should have the capability to come up with its own language as a means of processing thought through artificial intelligence training course. However, while this has been done by artificial intelligence processes in recent years, these languages still depend on and are based on the instructions given to these machines by humans.

As such, these machines will never be able to reach the same level of thought complexity that would be required to say, write a poem, or even understand empathy and a sense of belonging to the world. So in short, the answer to the question of whether artificial intelligence could become self-aware is, yes but only to an extent.

The likelihood of these machines reaching the level of thought complexity that humans enjoy is extremely less unless there is a breakthrough in our knowledge of how our minds work and we are able to translate that into the code for these computers.

What makes Hadoop so Powerful and how to Learn it?

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Why Hadoop?

With today’s powerful hardware, distribution capabilities, visualization tools, containerization concepts, cloud storage and computing capabilities, huge amounts of raw data can be stored, processed, analyzed, and converted into information, used for decision making, historical analysis and for future trend prediction.

Understanding Big data and converting into knowledge is the most powerful thing any entity can possess today. To achieve this, Hadoop is currently the most used data management platform. The main benefits of Hadoop are:

  1. Highly scalable
  2. Cost-effective
  3. Fault-tolerant
  4. Easy to process
  5. Open Source
  1. What is Hadoop?

Hadoop is a Highly distributed file system (HDFS), maintained by Apache Software Foundation. It is a software to store raw data, process it by leveraging the distributed computing capability and to manipulate and filter it for further analysis.

Several frameworks and machine learning libraries like python and Operate on the processed data to analyze and make predictions out of it. It is a horizontally scalable, largely distributed, clustered, highly available, and reliable framework to store and process unstructured data.

Hadoop consists of the file storage system (HDFS), a parallel batch processing engine Map Reduce and a resource management layer, YARN as standalone components. Open source software like Pig, Flume, Drill, Storm,Spark, Tez, Hive, Kafka, HBase, Mahoot, Zepplin etc. can be integrated on top of the Hadoop ecosystem to achieve the intended purpose.

How to Learn Hadoop?

With interest in Big Data growing day by day, learning it can help propel your career in development. There are several Big data Hadoop training courses and resources available online which can be used to master Hadoop theoretically.

However, mastery requires years of experience, practice, availability of large hardware resources and exposure to differently dimension ed software projects. Below area few ways to speed up learning Big Data.

  1. Join a course: There are several Big Data and Hadoop training courses available from a developer, architect, and administrator perspective. Hadoop customization like MapR, Horton Works, Cloud era etc. offer their own certifications.
  2. Learning marketplaces: Virtual classrooms and courses are available in Course Era, Udemy, Audacity etc. They are created by the best minds in the Big Data profession and are available at a nominal price.
  3. Start your own POC: Start practice with a single node cluster on a downloaded VM. Example: Cloud Era.com quick start.
  4. Books and Tutorials on the Hadoop ecosystem: Hadoop.apache.org, Data Science for Business, edurekha,digital vidya, are a few examples apart from the gazillion online tutorials and videos.
  5. Join the community: Joining the big data community, taking part in discussions and contributing back is a surefire way to increase your expertise in big data.

Points to remember why Learning Hadoop:

Below are the things to keep in mind while working on large open source Big Data projects like Hadoop:

  1. It can be overwhelming and frustrating: There will always be someone wiser and more adept than you are.Compete only with yourself.
  2. Software changes: The ecosystem keeps shifting to keep up with new technology and market needs. Keeping abreast is a continuous process.
  3. Always Optimize: Keep finding ways to increase the performance, maturity, reliability, scalability, and usability of your product. Try making it domain agnostic.
  4. Have Fun: Enjoy what you are doing, and the rest will come automatically!

All the Best on your foray into the digital jungle!

Why Knowing Python Is Essential For AI And Machine Learning?

Posted on by Imarticus Learning

Getting started in a field like machine learning or artificial intelligence can be a challenge. Due to the numerous coding mechanism sand tools available to help you program your potential AI software, using an open-source tool like python is considered an essential skill. Python is one of the easiest coding languages around today and is also one of the most versatile and wide-spreading tools available.

To learn Machine Learning and AI you will need a specific language. There are several languages that one can learn including C++, Java, and R. However, most industry experts agree that Python is one of the best places to start. It has a well-stocked library and comes with an extensive and diverse toolkit.

Here is a closer look at how you can chart your learning of Python for Machine Learning and AI.

  1. Learn the Syntax

Python is all about the various syntax. The good news is that you do not have to learn all of it. However, there is no getting around learning the basic syntax of Python. With this step, it is recommended that you do not spend too much time on it. A few days, up to a week, is enough to learn the basic syntax of Python as you can always refer to it later.

There are many places on the web where you can familiarize yourself with artificial intelligence courses including on the main Python website.Other web pages include Imarticus Learning who teach Python with learning data science as the end game.

What Is The Scope Of Business Analysis?

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The scope of the business analysis is all-encompassing as it works across the broad aim of business improvement with technology or without it. The spectrum of activities that fall under this field is a bit of management, finance, strategy making,dealing with both external and internal customers, ensuring regulatory and compliance issues are dealt with, strategising for better efficiency, cost analysis and everything that falls in between.

What Is The Future Of Business Analysis?

An uninteresting example is the development of the iPod. It was known that Hitachi had developed a mini-storage of 1 GB data capacity and was unable to take it to the market. At the same time, Apple had developed a music app that could not be used independently of storage capacity. Steve Jobs put these two together to produce the hugely popular invention he called the iPod. He was a successful entrepreneur.

The above success story can not only be inspirational, but it can also clearly demonstrate how a smart business analyst can use ML, AI, data analytics and predictive technology to create innovative products and steer the enterprise to success and huge profits.

Across the board, the last decade has seen technological advances and the replacement of repetitive jobs by AI. The need for business analysis and profits for the enterprise will never end. Technological advancements will also continue happening. However, most importantly the need for smart analysts with domain-expertise has far exceeded the supply.

Why Do Business Analysis Courses?

With technology implementation, most roles across various departments are collaborative and involve other teams and specialists across the organisation. The scope for experienced and tech-savvy business analysts’ roles is growing exponentially. The job role of the Business Analyst is lucrative and offers great payouts.

This role is one of the front line management roles responsible for a variety of management and strategy processes. The need of the hour is to have expertise in technology related to functioning. This would obviously mean acquiring a new skill set if you are employed or re-training those employees vital to the organisation.

Prerequisites:

A prerequisite to becoming a Business Analyst would be that you have a technological background (Ex: IT Graduates) or that you have relevant domain expertise (Ex: Commerce Graduates with knowledge of systems used). You will also need to have some relevant experience in the management of internal and external customers, as well as in assessing and analysing requirements, needs, and issues for which you need to develop workable solutions.

Business analysis courses:

Retrain and re-skill at Imarticus Learning. They offer an IIBA-endorsed and recognized Business Analysis Certification Program. The topics covered here help you gain the much-required expertise and immersive exposure to Business Analysis, and the technology powering techniques and frameworks on BABOK 3.0 which has recently been prescribed as the norm.

The best feature here is that you learn in real time on relevant projects by working on case studies, workshops,seminars and project work. You will thus have a well-rounded education and anew set of skills to handle multi-tasking with the best tools, techniques, and practices from industry-drawn certified trainers.

If you qualify, then don’t wait any longer. Retrain and upgrade your skills today.

Also Read: Why Business Analysis is Important Part of Business

How Companies Use Machine Learning

Posted on by Imarticus Learning

How Companies Use Machine Learning

Machine Learning and data processing has changed drastically the way things work inenterprises and even our daily lives. Digital technology has been able to enablemachines with ML software and algorithms to process intelligently and unsupervised the large volumes of data generated. The advent of the internet and such limitless uninterrupted data processing has generated many an error-free gainful insight.

Businesses can now transform to the high-efficiency mode where profits increase by creative use of employee time in using the insights and forecasts provided by machine learning, data analytics, big data processing, and accurate predictive analysis.

What are companies using ML in?

Learning and Scanning data images, text and voice: Repetitive tasks and tasks that are labour-intensive are now a one-step zero-error machine process. Digitizing data has scored in the following areas.

  • Data entry, documentation and report generation: The way data is processed, the volumes of data available, used and predictive analysis of data analytics have impacted lives and businesses to upgrade and upskill for better efficiency and profits.
  • Image Interpretations: Complex insights are possible with accurate predictive insights which have huge ramifications in the film, media, health, banking, insurance sectors and more.
  • Previewing videos: Data previewing in video form can help to process in speeds far higher than humans could ever think of. They can also match the videos to preferences of people, match advertisements to these, edit and curate video footage in fractions of a second! The advertising, marketing, media, film, and video industry has been transformed forever. The revenues generated with accompanied efficiency and speed has led to collaborations of machines and humans in a positive manner.

Uncovering and forecasting insights: ML has truly transformed the way we function with computers and ML replacing routine, repetitive tasks. Notably, the following sectors have improved tremendously.

Monitoring Markets: Mining of big data can result in time-saving and provides lead time in relevant and urgent monitoring of opportunities. News channels, competing in the business world, taking corrective actions and strategising have become a matter of nanoseconds with ML.

  • Root cause analysis: This technique used in production lines can predict and forecast failures of tasks, identify the root cause of the issues, suggest strategy changes required and generate alerts in these conditions.
  • Predictive maintenance: This tool is most effective in its forecasting abilities and ensures there will be no downtime in functioning.
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  • Predictive modelling: ML has enabled matching customer profiles and preferences to products available and browsing history-making auto-suggestions a routine affair. The huge potential of generating through advertisements matched to such preferences can generate more efficiency and high revenues.

With the advent and use of ML in everything you do, there is an urgent need for collaborators who can tweak software, create new applications, use the predictive and forecasting alerts and insights gainfully to improve profits, efficiency and save time, effort and costs. It is still early days and the right time to upgrade and re-skill with machine learning courses that will enable smart and creative use of machine learning benefits mentioned above.

Big data Hadoop training courses are also required to help ML understand and use the mind-boggling quantities of data that is now usable. Without the will to effectively use data and the training needed to adapt you will be left far behind. The situation today is adapt, or stay behind! 

How Will Imarticus’ Business Analyst Certification Course Help You Advance Your Career?

Posted on by Imarticus Learning

The market today has seen impressive use of technology in making use of artificial intelligence, machine learning, data analytics, and predictive analysis. All pervasive use of internet and smart systems like mobile phones, computers, use of virtual assistants, interactive apps, and so on, are everyday uses.
The Analytics and Financial Services sectors have ridden the wave of digitisation and are urgently in need of dedicated and experts in technological domains that did not exist a decade ago. Imarticus Learning caters to the aspiring needing tailor-made customized programs to further their career and prospects through skills up gradation with its innovative business analysis course in Bangalore.

Roles And Scope:

With thousands of jobs being advertised daily some with mind-boggling pay packets, a business analyst certification with Scrum and Agile BA can help in the following areas of professional empowerment.
Change management and its allied roles in Project Management, Business Analysis, Scrum and Agile suites, and SAP learning will equip and hone your skills to be able to successfully induce changes for enterprise success. Lucrative roles such as Scrum Master, Change Manager, Project Manager, or a Business Analyst could be yours with this skill upgrade.
In the role of a Business Analyst involvement in strategy and plans for change management and its implementation is crucial to the enterprise. Skills acquired here will help involvement with stakeholders and puts you in a pivotal role.
As a Scrum Master Agile helps you manage projects, overcome impediments, manage team health, eliminate wastage, manage self-organisation, apply process management tenets, and manage diverse cultures.

Why choose Imarticus Learning?

This enterprise provides:

  • The basic prerequisite is the will to learn and other secondary supportive qualifications
  • Have centres at Mumbai, where it is headquartered, Chennai, Bangalore, Pune, Jaipur, Delhi, Coimbatore, and Hyderabad
  • Online and virtual classroom instructor-led sessions pan-India
  • Training faculty includes mentoring expertise by veterans from the industry who are domain experts and share practical hands-on training through real-time scenarios.
  • Further core competency skill upgrades offered in evolving fields of technology.
  • Project work and use of real-time scenarios enable you to imbibe best practices and being industry-ready.
  • Believe in practice and hands-on training rather than theoretical learning of concepts.

Accepted certification and opportunities to better your job prospects and earn lucrative pay packets.
Business analysis classes with Imarticus includes:

  • Global and standardised curriculum that is offered internationally.
  • Building resumes that make a lasting impression and translate into landing lucrative job offers.
  • Open and private networks access for placements on the portal which provide opportunities, references and leads for successful placements.
  • Conduct of mock scenarios and interviews with panels for one-on-one training for these rounds through well-experienced and certified trainer instructors.
  • Preparation for interviews through well-researched questions to help clear the technical and HR rounds of your interview.
    Why wait any longer? Now is the time to enrol and upgrade your skill sets.
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