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Day: September 9, 2019

What Are Some Good Resources About Learning Financial Analysis?

Posted on by Imarticus Learning

What Are Some Good Resources About Learning Financial Analysis?

The spurt in the financial domain is instant, recognizing this trend people have started opting for a career in the finance industry. Building a career in such a competitive space where everyone wants a piece of the pie you have to have the added advantage to stand out the competition. The Financial Analysis subject is best suited for a budding finance enthusiast who is aspiring for a successful career in this field.
Financial Analysis is a complex subject matter that involves different fragments. You have to gather knowledge about a wide range of subjects. Financial reporting analysis, corporate finance, economics, equity, alternative investments, etc. are some of the prominent topics you’ll have to spend your time upon.
The subject matter of financial analysis involves a comprehensive understanding of the company’s fundamentals to do data analysis and project the future trajectory taking into account the different variables that might affect a company’s overall performance in the short as well as the long run.

Where to find good resources?

I am a firm believer of “learning can happen anywhere”, the catch here is that you got to have an open mind and a knack for learning the subject matter. Keeping attention to detail is a must in the case of learning finance.

Before deciding what resources you need to use for building your knowledge base in any domain, you have to figure out the ‘why’. Why do you want to learn financial analysis? The answers could vary from getting a job in a Financial firm to teaching others about the subject. When you have this answer then only you could establish the degree of knowledge that you need to obtain for your pursuit.
Learning is a continuous process and subject such as finance is always evolving with the economy and the world so there’s no end to learning here. What you knew a year ago might be outdated today so it needs constant catching up.
Today you’ll find countless resources to learn about any topic in finance. The world of social media has made learning easier and much more convenient than traditional means. The best resources can be found in the form of video channels on youtube, blogs, online courses, educational websites focusing on the finance niche, etc.

If you want to get a good job in the financial industry, getting validation for your knowledge is important, especially in the big corporate houses. You can opt for professional courses like CFA where you’ll get guidance on how to proceed in a structured manner for your financial analyst education. It is a course dedicated to financial Analysis, upon completion of the course and with relevant experience, you’ll get to use the charter title for a financial analyst.

Websites like coursera, udemy, edX provide students with comprehensive knowledge about the subject including test series and contextual subject matter which is updated to current standards.

If you break up financial analysis it contains two fragments one is involved with building your knowledge base in finance and the other is related to upgrading your analysis and presentation skills which include learning Ms excel and powerpoint.
You can even focus on learning the two fragments in isolation. You can opt for courses which teach excel and powerpoint and other courses which help you with building your financial & accounting knowledge.

There are various books on finance by popular authors which teaches financial education in a slightly unconventional manner. Some of the good reads are “Richest Man in Babylon”, “One up on wall street”. You can even find the ebook versions for the same on Amazon for a very minimal price if not free.

Conclusion
To learn financial analysis as a subject you need to figure out the details of the subject matter that includes topics from various subjects including economics accounting, financial maths, etc. It is important to define your goal for learning financial analysis that will give you a direction and will help determine the degree of knowledge you need for your particular endeavour. Online platforms like youtube have so many professionals teaching the subject matter, if you are looking for freebies it’s the best place. There are other educational websites like Coursera, and Udemy which provide a comprehensive courses and certifications for the same.

Also Read: How do I get job into Financial Analysis

Is A Machine Learning The Next Step Of Smart Learning?

Posted on by Imarticus Learning

Is A Machine Learning The Next Step Of Smart Learning?

2015 was rife with stories of ML and self-driving cars. Again a decade ago people were abuzz with robots doing the repetitive tasks, and human intervention being all about seasoned judgment for complex tasks. And then, cars were self-driven and computers really proved that they were fast approaching the machine learning course of human intelligence with self-learning algorithms and AI taking over a data-driven world.

Both AI and ML started with helping the human coded programs helping computers spot data patterns and inform algorithms which made foresight, insights, decisions and data-driven predictions. And then, the volumes of data became huge and machines needed a machine learning course to be able to help humans with cleaning and sorting the data.

 

So self-learning and deep learning algorithms soon taught the AI-driven computers to get smart and self-learn. As data became larger, their ability to accurately parse and clean data and provide insights increased. And so, we developed new self-learning ML algorithms which are the latest weapons against terrorism, cybersecurity, climate change, and cancer applications.

The Master Algorithm authored by Pedro Domingos, claims machine learning is the new basis and infrastructure for all applicational algorithms. He described it as the Higher Education switchboard. When data privacy became an issue in the UK in 2014 the US K-12 dialogue led to concerns in over-testing and by the end of the year, more than a hundred vendors of EdTech voluntarily signed the pledge for data privacy.

The series on SmartParents led with the argument that personalized learning is data-based and that parents with access to such data should decide on the privacy of the data. The policymakers were forced to embrace both data privacy and personalization.

Today ML and Big Data techniques are part of our lives and play a big role in informal and formal education. Let us see how we can make learning smart with machine learning. Below we list the areas and resources available to parents and teachers alike for

1. Learning data analytics and applications in a machine learning course that can help track student knowledge while recommending further learning steps. Here are some resources for learning systems that are adaptive.

Ex: ALEKS, DreamBox, Knewton and Reasoning Mind. Here’s a treasure for game-based learning:  Mangahigh and ST Math.

2. Beginning learning on content analytics that is used to optimize and organize content-modules.

Ex: IBM Watson Content Analytics and Gooru.

3. Scheduling for math learning that teams students needing help with teacher resources in real-time and dynamically.

Ex: NewClassrooms which uses ML and data analytics to schedule mathematics learning sessions.

4. Scoring and grading systems to score and asses on a large scale the student answers to the computer and other assignments and assessments: The grading could be peer grading or automatic ML grading.

Ex:  Lightside by Turnitin and WriteToLearn by Pearson help detect plagiarism and score essays.

5. To identify new opportunities through tools for process intelligence which analyze both big unstructured and structured data while enabling the visualization of work-flow.

Ex: Clarity from BrightBytes provides a strength gap analysis by reviewing best practices and research to build evidence-based frameworks.

IBM SPSS  and Jenzabar are systems for ERP-Enterprise Resource Planning which help the formal higher education schools and institutions in enhancing campus security, improving financial aid, predicting enrollment, and boosting student retention.

6. In helping match schools and teachers like TeacherMatch and MyEdMatch which harmonize online the recruitments of teachers.

7. For learning data mining and predictive analytics from experts try Map patterns of expert teachers and Improve learning, retention, and application articles.

8. For a host of applications in the back office are school bus scheduling EDULOG, Evolution, and DietMaster.

Parting Notes:

There is no doubt that the earlier you learn the more skilled you become. To ensure smart learning in ML every student and faculty member must learn at the earliest the impact of ML, AI, and Big Data. No matter what the pathway your learning curve should be enhanced with skills at the earliest.

Do you want to join a machine learning course at the Imarticus Learning Academy where data scientists hone their skills in AI, Big data and ML? Their courses also include personality development modules and train you in the soft skills required to emerge job-ready and with the right skill sets.

How A Blockchain Can Be Used In P2P Network?

Posted on by Imarticus Learning

How A Blockchain Can Be Used In P2P Network?

Making the blockchain technology decentralized is dependent on the peer to peer networks that are also known as crypto circles and their laying out and propagation as the base foundational layer. They are smaller networks popularly also called P2P networks that last forever and are the “censorship-resistant” factor of the blockchain itself.

P2P networks are no new concept with Napster the first popular network with over 80 million global users having to be shut down in 2001 because it allowed illegal music downloads. And from the remnants emerged BitTorrent the file-sharing system that is an active P2P network very popular today.

The Bitcoin network used both the secure transactions feature of the blockchains and the decentralized feature of the peer to peer networks. The network thus provided a zero-fee alternative financial system wherein the digital value was traded in as cryptocurrencies or virtual money. Bitcoin’s infrastructure layer and its subsequent success regenerated the importance of P2P networks as a viable method for the functional and technical protocols. This was quickly lapped up by many Fintech startups and enterprises that emerged using the success of the P2P networks.

Peer-to-peer blockchain networks are akin to social living organisms. They form an important of the infrastructure and consensual technology that they are dependent on. Transacting humans have to reach an agreement and publish the issue across the node-containing network for validation by providing the right solution to the poser. A large number of nodes ensures that the cooperation-based transactions of all participants generate the blockchain training resources that contribute to the evolution of the P2P network and is the key factor for authentication and validation of the transaction and users transacting.

The important benefits of the P2P network are:  

  • The permissionless number of nodes continues to be self-feeding and continuously growing.
  • The nodes are self-rewarding.
  • The self-governing progression promotes survivability and resiliency.
  • A degree of anonymity ensures the origin of work is hard to pinpoint.

The legal implications of the search function:

There will shortly come a time when the data on alternative P2P networks like the traditional searches on Google or Googling will be large enough and revealing or trading in decentralized content will be a fact. Unless Google updates their security, such content will find its way into the hands of crawlers who will make the discovery of decentralized content easy to achieve.

We also need to be aware of the consequences of the ethical, moral, and lawfulness aspects of decentralization of blockchain training in P2P networks. What would happen if the unstoppable P2P networks get used for the wrong and illegal? Has anyone found a viable solution for clearing the stable of offensive and illegal content and punishing the creators or originators of such wrongful use of the P2P networks? At some point in the recent past, this was the issue with the Internet being used for immoral and illegal uses.

Yes, there will always be the few rotten apples who will use any means to achieve their goals be it the internet, blockchains or satellite P2P networks. But let us not forget the example of Napster which was forced to shut down for infringing on the rights of musicians by allowing illegal downloads. Or the Craigslist was forced to take down their Personal section after the US Congress Bill held them responsible for facilitating and promoting the prostitution of other persons and sought to levy 10 years imprisonment, fines, and such enal action if it was not closed out. Someone clearly let Google get away with the exact same behaviour!

The future of the unstoppable and viable P2P networks can’t be compromised as they are the building blocks for the next-gen functional blockchain training capabilities, decentralized protocols, and P2P applications. The time is not far away when multiple P2P networks will use blockchains for validation, decentralized identity-linked networks for security, and another P2P network for storage.

Conclusions:

Important questions persist regarding whether the P2P unstoppable networks will be used as a tool for good reasons and benefits or as a weapon in the hands of the bad for illegal, corrupt promotion of causes. It is hoped that most of the applications will emerge on the just and right side as the new and powerful tools of the future. If you want to learn more about the way P2P networks and blockchains function you could do a blockchain training course at the reputed Imarticus Learning Academy. Why not start now?