September 24, 2021 - Finance, Tech & Analytics Career Resources

Why Are Companies Considering Candidates With An Artificial Intelligence and Machine Learning Certification?

Posted on September 24, 2021April 1, 2024 by Imarticus Learning

Artificial Intelligence has expanded at an exponential rate in recent years, despite significant progress in the field. In the field of computer science, AI practices can be found everywhere. It provides you with an idea of how many different ways a computer system can be designed.

It is designed to carry out the cognitive functions that humans have specified.

This indicates that the scope of an artificial intelligence and machine learning course is enormous, and AI has potential that is currently beyond human grasp.

Scope of An Artificial Intelligence and Machine Learning Course in India

Artificial Intelligence has enormous potential to transform every sector of the economy for the greater good.

AI encompasses a wide range of technologies, including self-improving algorithms, machine learning, big data, and pattern recognition, to name a few. There will be few industries or sectors left unaffected by this potent weapon in the not too distant future. This is why online Artificial Intelligence courses are becoming increasingly popular in India.

With each passing day, the gap between the number of AI professionals required and those available widens. Corporations are spending money to train their existing employees on Artificial Intelligence technologies. However, the demand is far higher.

Learn AI

Certification In Artificial Intelligence & Machine Learning

Learn AI via 25 in-class, real-world projects focused on offering exposure to various industries. This 9-month program will help you prepare for the roles of Data Scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

This machine learning certification program was established in collaboration with the E&ICT Academy, IIT Guwahati, and industry professionals to give an optimum learning outcome,

This course will strengthen your core abilities, allow you to take advantage of our Expert Mentorship program, and give you a practical grasp of AI and Machine Learning.

Data Science Prodegree

Develop your knowledge of Data Science ideas and build robust models to generate relevant business insights or forecasts with a working knowledge of critical Data Analytics technologies such as Python, R, SQL, and Tableau in these 14 in-class and industry-oriented projects.

PGP In Digital Marketing

Our Digital Marketing Postgraduate course is meant to provide you with a more in-depth and practical understanding of Digital Marketing ideas. The postgraduate program takes a collaborative approach that emphasizes several Capstone projects, job-specific skills, and guaranteed job interviews.

This course will prepare you from beginning to end to start or advance your career in the Digital Marketing segment, including resume building, mock interviews, job leads, and references,

making it an ideal Digital Marketing course with a strong focus on placements to help you land your dream job.

Post Graduate Program in Data Analytics & Machine Learning

This machine learning certification program is for recent graduates and early career professionals interested in pursuing a career in Data Science and Analytics, the most in-demand job skill.

To become job-ready, master the fundamentals of data analytics and machine learning, as well as the most in-demand data science tools and methodologies.

With this job assured program, you’ll learn Python, SQL, Data Analytics, Machine Learning, and Data Visualization. After completing the course, students are promised interview opportunities.

Takeaway

AI is one of the most popular technologies on the planet because of its diversity and superior solutions. It has been rapidly expanding. As you can see, the scope of AI has broadened to include a wide range of industries, including healthcare, transportation, security, etc. Multiple industries require the expertise of experienced AI specialists as a result of this increase.

Check out Imarticus IT classes, targeted at working professionals, if you want to learn more about AI and machine learning algorithms.

How can a software engineer become a blockchain developer?

Posted on September 24, 2021March 21, 2024 by Imarticus Learning

As a breakthrough technology, blockchain has undoubtedly spawned a new branch of development, known as blockchain development. As a result, there are a plethora of work prospects for developers and tech aficionados. Many people look for jobs after completing a certification in Software Engineering.

The two kinds of Blockchain Developers are:

Core Blockchain Developers
Blockchain Software Developers

In most cases, a Core Blockchain Developer is engaged in the design, architecture, and security of a blockchain system.

Blockchain Software Developers have their own set of responsibilities. These responsibilities have nothing to do with the system’s consensus design or architecture. Blockchain software developers use blockchain technology to build decentralized applications in the same way that a regular web developer uses the protocols and architectural structure established by a core web architect to build web apps.

As blockchain technology and its myriad applications gain popularity, a slew of new opportunities for software developers emerge. The blockchain developer is in a high-level position in the industry. However, because it is such a unique profession, the role is not as well-defined as other tech positions that have been on the market for a long time.

This is because a blockchain developer can be any software engineer who is qualified to work with blockchain technologies. Plus, since blockchain works closely with cloud systems, a Cloud DevOps Engineer training can also help in setting up the systems. A software engineer/Cloud DevOps Engineer can help in this regard.

How can a software engineer turn into a blockchain developer?

Any software engineer may become a blockchain expert. Furthermore, the vast majority of blockchain specialists began their careers as programmers or software engineers. As a result, you can receive a standard software engineer education while also taking various specialist courses on blockchain technologies.

To flourish as a blockchain developer, you must be well-versed in essential programming languages utilized in blockchain projects. Javascript is one of the most often used programming languages in blockchain projects. Solidity would be another important language that will give ambitious developers a leg up.

It is one of the few languages to concentrate on because it is the language of Ethereum’s smart contracts. Python, Java, and Clojure are some major languages utilized to develop the majority of blockchain applications around the world.

Blockchain is synonymous with security. Furthermore, cryptography assures that blockchain networks are impenetrable. It is the branch of engineering concerned with active and intelligent opposition. Being a cryptography expert will improve your blockchain development skills as it will allow you to encrypt decentralized records, which in reality is the foundation of blockchain.

The ability of a blockchain developer to tinker with data structures to get desired results is critical to the project. As a result, as an aspiring blockchain engineer, you must grasp the applications of data structures in order to achieve exponential results in your future projects.

Blockchain projects also include UI design, request handling, and Application Programming Interface Management. Most of these tasks are performed by experienced engineers; however, full-stack web development knowledge will add extra points to your profile. It also gives you a tremendous head start because you will already have the skills needed to function in larger roles.

Here are some tips on the skills to acquire that have been laid down by IBM:

Learning the basic database technology is useful for understanding blockchain and, in particular, data structures.
Learn how to create digital assets, how to preserve them, and how to retrieve them.
Gain knowledge about distributed computing, network formation, and how to interact and send data across point A to point B.

Conclusion:
As evident from this article, the job of a blockchain engineer is very much in demand these days. Hence, a certification in software engineering course might just be the right boost you need in order to bag placement in a good firm. Blockchains are also being used in IoT networking, and software engineers can help in integrating blockchain systems with IoT networking.

Data Analytics, Productivity, and Well-being: Are they interrelated?

Posted on September 24, 2021September 30, 2022 by Imarticus Learning

Forms and benefits of data analytics have shifted majorly in the last few years. Major firms have also been using it as a way to decipher the habit patterns of their employees to take care of their well-being. Needless to say, their wellbeing directly relates to their workplace productivity. However, with the evolution of data analytics, data analysts also have to be able to evolve constantly.

And that is only possible when they have the proper training to adapt to situations, and that can only happen if they learn data analytics from a proper institution. Imarticus Learning has come forth with a great opportunity for people who would like to polish their skills with their new PG program with data analytics and machine learning certification.

Coming back to the impact of the well-being of employees on company productivity, studies have found that being comfortable in their workplace can make the workers about 12% more productive.

Data analysis as a tool to ensure happiness

Major firms have been trying to gather and decipher the patterns of their employees’ behavior to provide a personalized experience to them for some time now. There are a lot of ways companies have decided to approach it. Some offered wearables to their employees that will teach how much time they spend, sitting, talking, writing, or moving about. Some have chosen the company intranet to trace their online tracks.

Now it falls to the data analytics team to extract, and decipher these patterns. It is fruitful in the sense that these patterns always give indications of not only their physical health but also their mental ones. This is also a way where companies can provide personalized suggestions for their well-being. And the employees get benefitted from it in a way that impacts their daily life. As a result, they feel more loyalty towards the company.

Hurdles to jump over

There are some evident advantages of exchanging data for the betterment of the employees’ wellbeing, and in turn, increase their productivity. However, it is also a possibility that when it comes to data gathering and analysis, the employees might have some privacy concerns about them.

Which in turn, might make them unwilling to participate actively in the bandwagon. This is why, there are a few things that should be kept in mind when it comes to the interrelation of wellbeing and productivity of the workers, such as:

The first and most important thing is to make sure the workers consent to the exchange of data for the company’s use, as many might have privacy concerns relating to that.
Companies will need to have experts in the analytics team to properly extract and use the data and make it a priority for both the main wing of the business and the analytics team to prioritize the employees well being.They need to communicate properly to the workers how it benefits them and the company both at once.
The key is to recognize what the employees want and be able to cater to it. Otherwise, even after using data analytics to define the workers’ needs, it will be utterly irrelevant.

Conclusion

Using data analytics as a mode of communication between the employer and employee needs time and expert skills. And it can only come if you learn data analytics from a good place. Many institutes in India offer a data analytics certificate course. Imarticus Learning is one of the topmost among them, so do check out their PG program of data analytics and machine learning.

Fuelling Business Growth and Innovation with Investment Banking Operations

Posted on September 24, 2021April 1, 2024 by Imarticus Learning

Investment banking is that division within the banking sector that facilitates large capital funding for corporations and governmental bodies. Common perceptions make us immediately associate investment banking with Harvey Specter like bankers assisting corporations to crack high stakes negotiations and deals. But there are massive backend operations going on at all times without which these deals would be impossible.

That is the importance of investment banking operations. An operational investment banker, more commonly referred to as an operations specialist, is responsible for ensuring efficiency, accuracy, profitability, and risk reduction vis-a-vis the clearance and settlement of transactions for the company’s clientele.

Utilizing investment banking operations to their full potential engsures infinite business growth and innovation. Which is all the more reason why operations is an extremely lucrative career path.

In this article, we discuss the ways in which business growth and innovation can be fuelled with investment banking operations as well as provide recommendations for investment banking online certification and investment banker courses in India for anyone looking to learn investment banking to improve their career prospects.

Function Of Investment Banking Operations

Investment banks offer transactional, legal, and advisory services to their high-profile clientele with complex financial needs.

Some of the activities included in the oeuvre of investment banking are underwriting, mergers and acquisitions, equity research, and asset management.

During the processing of transactions, there is a huge volume of information, products, and money that continuously flow from end to end. The smooth processing of this data falls under the jurisdiction of the operations teams which is also referred to as the back office or engine room in investment banking parlance.

Apart from providing support to client-facing departments, the operations staff also ensure the optimal functioning of IT solutions and data management systems deployed across the organization. They also oversee the regulatory requirements of a bank.

Driving Growth Potential With Investment Banking Operations

Investment banks play a pivotal role in sustaining the larger economy by adding liquidity to the financial markets. They promote business growth and aid the circulation of money in the economy thereby promoting growth. Banking operations are the dark knight of any investment bank – the heroes who hide in plain sight. Although, they perform non-revenue functions, without them the profit-making capacity comes crashing down.

Think of it as having a strong core. No matter the amount of muscles one grows in the arms or legs, without a strong core, the body is unable to support or balance them. Streamlined banking operations can save banks tons of money which can then be utilized for business growth and building innovations.

How To Be An Operational Investment Banker

There are several roles and functionalities under the banking operations of an investment bank. New entrants usually undergo extensive on-the-job training for at least one to two years that helps in the development of niche expertise.

Hiring teams in investment banks look for formal education in finance and internship or apprenticeship experiences in potential candidates. Having an investment banker online certification also adds to a candidate’s competitive edge.

Conclusion

To learn investment banking, a good place to start is to get a degree from any reputed institution in India. A Certified Investment Banking Operations Professional course from a good institution can be the best investment banker course in India that can guarantee a CIBOP degree and best job interview opportunities.

If a classroom environment seems uncomfortable in the post-Covid world then you can also consider this online Certified Investment Banking Operations Professional course that offers holistic learning in the nitty-gritty of investment banking operations.

Which Is Better For Machine Learning R or Python?

Posted on September 24, 2021October 15, 2021 by Imarticus Learning

Machine learning is not a single science. It comprises a blend of fields such as analysis, recognition, prediction and decision making. There are several open-source tools available for machine learning out of which R and Python are the most demanded or rather the most popular ones. The main difference between the two languages has been seen in the fields of analysis and data science.

Both the languages provide open source tools and support from a wide variety of libraries for machine learning but because of the high degree of robustness provided by the python packages such as Scikit-learn built on numpy and Scipy, Python is preferred more for machine learning. According to a recent survey, Python had an increment in its popularity and use from 53% to 69% within two years.

Several machine learning courses aim at delivering courses dedicated to R and Python. The question as to whether an individual should learn both languages depends highly on the field of application and interest of an individual. Both languages have highly efficient ecosystems for machine learning tasks.

The difference in popularity and use is because of the comfort of an individual with the programming language, interest and application needs. Also, job opportunities can be one of the deciding factors whether an individual should learn Python or R for machine learning.

Provided below is a comparison of Python and R which could help an individual decide whether they need to learn both languages.

R was developed by the statisticians primarily for analysis. The programming language is based on the mathematical calculations comprising machine learning and hence forms a really important part of the statistics involved in the project. Thus, a project which is largely dependent on statistics should use R as a programming language.

Advantages:

Highly suitable for data analysis and visualization.
Support from the libraries
Highly robust
Highly suited for exploratory work

Disadvantages:

Scarcity of expertise in the language due to low learning rates.
The algorithms in R comes primarily from the third parties and hence, it is not very consistent to build the models.

Python:

Python came into existence in the ’80s. Today, it forms a core of the machine learning operations being performed by Google. It has extended its roots in the field of artificial intelligence as well and is being widely used in almost every possible domains whether technical or non-technical.

Advantages:

In contrast to R which provides support for only statistics, machine learning has extended beyond just statistics.
Python unlike R provides a smooth learning curve and is more consistent than R.
Huge support from libraries such as numpy, pandas, OpenCV, sklearn, etc.
Simplicity in the syntax making it easy to learn the language.
Highly robust models and boosting techniques.

Disadvantages:

Less support for statistical models due to the non-availability of suitable packages.
Multithreading is Pyhton is not generally preferred as it is difficult to implement.

From the above comparison, it can be seen that both the languages having their advantages and disadvantages. But the key point that differentiates them is the use and library support. R and Python in machine learning have succeeded in their way. One has left footprints in the field of analytics while the other has emerged victorious in the field of data science.

Conclusion

To choose the right language, the right strategy is needed. For a person stepping into the industry as a fresher, Python is preferred as compared to R because of its simple syntax and ease of learning.

Also, if an individual is looking for a career in the field of data science they should go for Python as the programming language and if they want to handle the huge data-related tasks such as analysis and prediction making, no doubt that R is a better choice.

R is closely related to analysis and Python is closely tied to huge tasks such as object detection, disease prediction, computer vision and so on. Hence, we can conclude by saying that an individual needs to rightly assess their needs before choosing one of them and should master only one trade.

Day: September 24, 2021