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From Executives to Executives – Executive Management Training at Imarticus

Posted on by Imarticus Learning

From Executives to Executives – Executive Management Training at Imarticus

Whether you’re looking to develop leadership skills or boost your career, executive management training can help!

Explore Imarticus’ range of business courses as corporate training programs for employees to enhance your leadership skills and develop the knowledge you need to succeed. The course covers everything from basic to advanced topics such as leadership skills, team building, and project management. You can develop and improve your skills and abilities through these programs.

For more information, refer to the article below.

Need for Executive Management Training Courses

The Executive Management Training Programs have traditionally assisted professionals in gaining the knowledge and comprehension of the leadership abilities necessary for their current and future jobs. They become more robust, resilient, and agile thanks to these programs. Enhancing the CEOs’ capacity for leadership encourages business expansion.

Productivity at work increases for newly trained leaders and their entire team. Each person strives to use their leadership style to develop a productive team. They seek to inspire their group of employees in a unique style that fits their personality. After carefully examining their strengths and flaws, they can develop their leadership tactics thanks to these training sessions.

Today, data analysis is used to inform critical business decisions. Not only inexperienced but also seasoned corporate leaders frequently struggle to manage a large amount of data. Because of this, data analysis has become a crucial component of executive training programs in 2022.

executive management training

As firms adopt artificial intelligence, new challenges are quickly surfacing. The training programs for CEOs equip them with the adaptability and skills needed to meet these technological challenges.

The long overdue need for women in leadership is being addressed via exclusive corporate development and training.

Special Features of Executive Management Training Courses

Customised executive management training is available

One of its main benefits is an executive management training program’s ability to be offered after a one-on-one consultation with the institution looking to run the program. Many conferences, books, video libraries, and online programs fail to make sense to the participants because their skill sets are not considered when the programs are offered. Training in executive management with Imarticus resolves this issue.

An academically sound curriculum

While the media is busy reporting on the newest trends in training, practical learning in Imarticus comes from a well-researched curriculum. Employee motivation to take on today’s difficulties will be significantly increased by a curriculum created in conjunction with the industry and aligned with the digital era.

Improves the employee’s alignment with the business

Employers have difficulty getting their message across to their staff. Aligning their executives with the corporate objectives is a continuous exercise. Completing an executive management training program that aligns with the corporate goals is one of the most acceptable ways to do this. Employees will acquire such aptitudes from the executive management training in Imarticus that will assist them in aligning with the company’s objectives.

Prepares the upcoming generation of managers and leaders

An organisation might provide executive management training for workers who will hold managerial positions. A successful business needs managers who have completed a lead management program. Through team-building exercises and presentations, executive management training instils a crucial leadership attitude in its participants.

Performance within a company is influenced by a variety of factors, including staff skill sets and training. This is one compelling reason to carefully weigh the benefits of various employee training possibilities. Imarticus recognises that executive management training programs have a wide-ranging impact when people assess them. The best option for staff training is executive management training for several significant advantages it holds.

Conclusion

Imarticus Learning has run programs for some of the giant corporations of the world and is aware of what it takes to upskill workers so they can compete taking a lead in today’s market. So, Human Resource teams, Learning and Development Heads, and other management officials thinking of including executive management training in their organisation can choose Imarticus without any dilemma and get the best results in a brief period.

How supply chain analytics are enabling organisations to become more efficient

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How supply chain analytics are enabling organisations to become more efficient

With the growing competition in the market every organisation tries to enhance their company’s effectiveness to its maximum potential. Supply chain analytics enables organisations to strategise their business and carry out predictive planning that could benefit their sales and bring in maximum profit. In this article, we will explore how supply chain analytics benefits companies and why you should choose a career as a supply chain analyst.

What is Supply Chain Analytics?

The work of supply chain analytics is to produce insights, recognise patterns, and assess the information provided by the supply chains. This information or data is extracted from the supply chain execution systems and the management of inventory, order, warehouse and transport. 

Here’s a brief account of the four basic supply chain analytics that enables organisations to build more profitable operations to increase their efficiency:

  • Descriptive analytics 

This assists in providing visibility to the suppliers and analyses the past sales data extracted from both the internal and external supply chain execution systems. This enables the suppliers and all the other sales channels to draw comparisons through the historical data and recognise the changes in the present status of the sale and understand the reasons causing them.

  • Predictive analytics 

Predictive Analytics enables companies to analyse future events and their possible impact on the business. This helps the companies to eliminate risks and prepare effective plans and strategies to deal with any disruptions in the future and act accordingly.

  • Prescriptive analytics 

This takes into account the outcomes of both Descriptive and Predictive Analytics and puts forward suggestions that help the company mitigate any kind of disruptions. It provides better ways to tackle problems by interpreting the data of their own business activities along with their partners. 

Why choose a career as a Supply Chain Analyst?

best supply chain management and analytics courses

A career in supply chain management is very steady and lucrative. It has a lot of opportunities and provides growth and employee satisfaction. The SCM Imarticus is a professional supply chain management online training platform 

Which provides various supply chain management certification course options that will help you learn all the know-how and open doors for you in the field of supply chain management.

Following are the ways in which Supply Chain Analytics benefits organisations and increases their efficiency:

Data transparency in the supply chain management

The supply chain analytics helps in improving data visibility for the organisations helping them in making informed decisions to enhance their supply efficiency and also analysing what went wrong in the business and how to improve their supply chain management system.

Mitigation of risks and other liabilities 

Supply Chain analytics analyses the potential risks in the future and also suggests ways to avoid those disruptions which help the companies to prepare themselves to tackle any challenges and liabilities associated with supply chain management. 

Cost-effective management

Supply chain analytics eliminates the manual tasks like accounting, data entry, or calculative works which were done by the human workforce. This helps in cutting down costs and also produces more accurate data and billing practices at the same time. 

Selection of better partners

Supply chain analytics provides information about the vendors, their way of handling the business and how relevant they are in the business. This helps the supply chain managers to select partners who are a good fit for the company and can increase its efficiency.

Demand prediction

Supply chain analytics predicts the growing trends in the market to ensure the meeting of the demands of the consumers. It helps the companies to determine what products should be stored as they can bring in more profits and what can be minimised.

Efficient flow Of products

Supply chain analytics ensures an effective flow of goods as it regulates every facet of the supply chain by using its tools and features. It also enables better communication in the supply chain which mitigates the issues of cost and improves the relationship between suppliers and customers.

Conclusion

Supply chain analytics has become one of the most essential elements in supply chain management and uses its technological infrastructure to increase efficiency in the supply chain. It helps in the profitable and accurate planning of sales, improvement in the risk and order management system, and brings in profits and consumer conversions at the same time. There are many supply chain management certification courses and supply chain management online training available that can help you build a profitable career in this field.

Machine Learning For The Curious: Placements made easy

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Machine Learning For The Curious: Placements made easy

You can use curiosity as a strong motivator to your advantage. We all share a fundamental human quality to varying degrees: a desire to learn more. In this course, we will explore machine learning, an exciting field that has been fundamental to the development of AI. We will introduce some key concepts such as neural networks, deep learning, and more to understand how these technologies work.

Machine Learning for The Curious

The Machine Learning course will teach you how to build a machine learning system from scratch. In this course, you’ll learn the theory behind machine learning, how it works, and practical applications of the technology in real life. You’ll also get hands-on experience with several different ML algorithms: linear regression, Naive Bayes classification, and matrix factorization (also known as PCA). 

Techniques from other disciplines cannot duplicate the capabilities and outcomes produced by machine learning methods, and if they could, they would refer as machine learning. Machine learning techniques differ from other techniques in two ways:

  • They are applications that use data to learn.
  • They are programs that produce programs to solve issues.

What Is The Difference Between AI, Deep Learning, and Machine Learning?

  • AI is a general term used to describe machines capable of exhibiting intelligent behavior.
  • Machine learning is the application of AI to create machines that can learn from data and make predictions. It is the most widely used technique in machine learning, especially in deep learning (DL) systems.
  • Deep learning is a form of machine learning and artificial intelligence (AI) that resembles how people learn specific subjects. Data science, which also includes statistics and predictive modeling, includes deep learning as a key component. 

Machine learning: A fascinating field

It is a branch of AI (artificial intelligence) that enables computers to learn from data. It’s also called statistical modeling because it uses algorithms to predict future events based on past ones. Machine learning gets used in many applications, including computer vision, natural language processing, and speech recognition.

Programs that use machine learning learn from examples, which makes it fascinating. A machine learning method can automatically analyze and understand the structure of the data you have collected to solve the problem you are trying to solve.

Discover a career in data analytics with Imarticus Learning

online learning

With this machine learning course, students can become data analysts and receive job offers. Learn machine learning using data science that produces vital business forecasts and insights by applying your new knowledge to practical use.

Course Benefits for Students:

  • The most widely used data science tools and methodologies, as well as data analytics and the fundamentals of machine learning, will be familiar to students.
  • To receive a data analytics certification course, students must complete 25 real-world projects and case studies directed by business partners.
  • Using a data analytics tool to display data is one of the most in-demand skills in the market. Therefore, recent graduates and those starting their careers might want to think about enrolling.

 Contact us through the chat support system, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Hedging Exchange Traded Products in a Derivative Market

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Hedging is the process by which an investor, or a market participant, seeks to reduce the risk of a particular investment position. Some hedging strategies include selling and buying options and using futures contracts or other derivatives.

What is Hedging?

An effective way to guard against losses is to hedge. In the financial markets, using derivatives to protect your position on an underlying asset is quite common. Financial instruments known as derivatives get their value from underlying assets like stocks or bonds.

Types of Hedging

Hedging is a way of reducing risk. It can reduce the risk of price fluctuations or the possibility that your investment will lose money. For example, if you want to buy an asset at $10 but the price goes down to $8 before you can sell it, then hedging would help protect against this loss. In this case, if there was no hedging mechanism in place and someone invested $10 into buying a share of stock and then selling their shares for $8—they would still have lost
money overall because they didn’t make any profit from their initial purchase price
point.

The most common type of hedge involves using derivatives—which are financial instruments whose value depends on something else other than themselves, such as stocks or bonds—to reduce exposure when markets fluctuate wildly from one day to another, primarily due to uncertainty over future events such as interest rates rise
faster than expected or inflation dropping unexpectedly low.

The Derivative Market: What Is It?

The financial market for financial instruments based on the values of their underlying assets is known as the derivatives market. These could include stocks, indices, currencies, commodities, exchange rates, and interest rates.  Over time, these products have evolved into more complex financial instruments like ETPs and interest rate
swaps—are still growing today!

Hedging ETPs in a Derivative Market

The exchange-traded product (ETP) is a type of derivative that allows you to trade financial instruments like stocks and bonds. You can also use an ETP to hedge against losses on your portfolio by taking advantage of the market & upward momentum. Hedging is the practice of reducing the risk of an investment. In simple terms, it means
you are taking on a position that helps offset your exposure to price movements in the underlying product.

For instance, if you own a stock and want to hedge it with another asset (e.g., bonds), you might sell them short and buy puts on another stock with similar characteristics. This way, if there is any decline in value in one asset (say your shares), it will offset some or all of these losses by having covered some positions through selling puts on
other stocks with similar characteristics as yours.
corporate leadership
Learn investment banking courses with Imarticus Learning With the help of the Certified Investment Banking Operations Professional program, students can begin a career in derivative markets. Students who complete this investment banking certification program will have the skills and knowledge necessary to succeed in banking, treasury, and clearing services at all stages of production.

Course Benefits for Learners:

 Students will gain knowledge of financial services, including managing complex securities and derivative products and their trade-life cycles.

 Students may be able to get the assistance they need to start careers in investment banking.

 Students who complete the derivative markets online training and money market course will receive an industry-recognized certificate.

Contact us through chat support, or drive to one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Does every computer science degree require cyber security training?

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In an era where we depend on computers and other cyber technologies for almost anything, cybersecurity is of paramount importance. We have seen an exponential rise in the number of cyber security scares globally in recent years. The 2022 Thales Data Threat report states that there have been more than a thousand cases of data breaches globally in the past 6 years.

From the Equifax breach of American citizens’ private information in 2017, Russian cyber interference in the 2016 U.S. presidential election, to frequent breaches in Facebook servers, we have seen data of millions getting leaked.

We are living in an era in which data is deemed to be the most expensive commodity of our time. Yet, there is a lack of consciousness and security when it comes to protecting our private information and data. Imarticus Learning has come up with a 6-month extensive cybersecurity course that will train young professionals about ethical hacking and penetration testing. This article will give you a cursory understanding of why every computer science degree requires cyber security training. 

What is cybersecurity?

The practice of safeguarding sensitive information and critical systems from digital viruses and attacks is known as cybersecurity. It is the application of controls, processes, and technologies to protect data, devices, networks, programs, and systems from online hacking and other viruses.

Also known as information technology (IT) security, it strives to diminish the threat of cyberattacks and defend against the unauthorized exploitation of networks, systems, and technologies. Cybersecurity measures are protectionary measures designed to combat threats, both from the inside and outside of any organization, against networked systems and applications. 

Domains of cybersecurity

A proper cybersecurity strategy will address the innumerable domains present in the cyberworld vulnerable to cyberattacks. It will have layers of protection to defend against all types of cybercrime, not limited to attempted hacking to access, change, or destroy sensitive data and information, cyberattacks that aim to disrupt business operations, or extort money through fraudulent measures. 

  • Critical infrastructure security: This is the practice of protecting computer networks, systems, and other assets on which economic health, national security, and public safety rely. The U.S. Department of Homeland Security (DHS) has collaborated with the National Institute of Standards and Technology (NIST) to create a cybersecurity framework that helps business organizations in this issue.
  • Network security: These are security measures designed to safeguard any computer network from malware, including wired and wireless (Wi-Fi) connections.
  • Application security: This security measure is in-built into applications at the designing stage while considering user authentication, data handling, etc. It helps to protect cyber applications operating in the cloud or on-premises.
  • End-user education: This practice aims to create security awareness to amplify endpoint security across the organization. For example, you can train users to evade using unknown USB devices, ignore and delete suspicious email attachments, etc.
  • Disaster recovery/business continuity planning: This security measure came in quite handy during the global pandemic. It comprises procedures and tools to respond to unexpected events, such as cybersecurity incidents, power outages, and natural disasters, with minimal disturbance to primary business operations.

Primary cybersecurity practices

Some of the best cybersecurity practices you can implement in your network to enjoy strong cybersecurity and minimize the risk of facing vulnerable cyberattacks are:

  • Identity and access management (IAM) depicts the access privileges and roles of each user. It also defines the circumstances under which they will be granted or denied their privileges.
  • A complete data security platform safeguards sensitive data across multiple environments, including hybrid multi-cloud environments.
  • Security information and event management (SIEM) analyze and aggregates information from security events to automatically catch suspicious user activity. It will then trigger a remedial or preventative response. 

Conclusion

In this age of information, every company requires a cybersecurity analyst who not only knows the technical know-how but also understands the importance of cybersecurity. There is a huge demand for such cybersecurity analysts and Imarticus Learning has introduced cybersecurity courses online to help young professionals enter this prospective field. 

Understand Amazon’s Supply Chain

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Understand Amazon’s Supply Chain

If you are thinking of a supply chain management career, then you must learn how experts from different industries plan and execute their supply chains. One example of supply chain management that you can refer to is the American multinational e-commerce giant Amazon which has become a household name by winning the trust of millions of its customers.

Amazon made its debut in 1994 as a book-selling website. Today, it features one of the largest and most efficient supply chain models ever seen around the globe. How did Amazon achieve this? What are the fundamentals it focused on for the management of its supply chain? Let’s find out!

Before we get into the details of Amazon’s supply chain, an aspiring supply chain professional like you needs to get the conceptual basics correct so that you can understand these real-life examples well and in their entirety. 

For this, you may wish to enrol in our IIT Supply chain management certification course which equips you with the fundamental concepts of the field that are necessary for making data-driven strategic business decisions!

All About Amazon’s Supply Chain

Amazon’s Supply Chain refers to the entire process under which a product on offer by Amazon undergoes in its life journey. This is the process that starts right from the moment a product reaches Amazon’s warehouse, enters its inventory records, and goes on till the time it gets delivered to the customer.

To offer a robust platform to its suppliers, Amazon provides them with two types of fulfillment options – 

 

  • Fulfillment By Amazon (FBA) – Under this option, Amazon is responsible for storing, packaging, as well as shipping the product to the customer.
  • Fulfillment By Merchant (FBM) – Under this fulfillment option, the responsibility of storing the products in the warehouse, packing, and shipping them to the customers rests with the Merchant.

 

How Does Amazon Supply Chain Work?

Over the last 2 decades, Amazon has made several changes to the working of its supply chain, in a bid to crack an efficient system with which it can offer the fastest delivery options like same-delivery to its customers. 

As soon as Amazon receives an order, products get arranged into pallets either manually or with forklifts into the warehouses, where they get packed and screened for quality checks. After receiving a go-ahead from clearances, Amazon’s logistics team enters the supply chain and completes the delivery of the orders.

To achieve this efficiently, the e-commerce conglomerate puts its primary focus on two elements of the chain – Storage and Delivery. Let’s uncover how Amazon takes care of these two areas.

  • Storage 

Amazon has more than 20 Crore customers globally who have subscribed to its Prime membership, which means, it needs to deliver a huge number of its orders in just 1 day or a maximum time of 2 days.

To fulfill this promise of fast delivery, Amazon maintains a huge network of fulfillment centers for storing its products. Amazon currently has 185 fulfillment centers spread across different cities of the world with a carpet area of up to 10,00,000 square feet!

This huge storage capacity helps Amazon maintain a cutting edge over its competitors and maintain a smooth fulfillment of its orders. 

Another important aspect that Amazon has taken into consideration for its warehousing is its location. Most of its fulfillment centers are located near metropolitan cities from where it received huge and regular demand.

Moreover, to speed up warehouse operations, Amazon has deployed over 10 Lakh employees in its fulfillment centers globally. It also uses robots, drones, and other high-end technologies to run its warehouse ecosystem with greater efficiency. 

  • Delivery

The second most crucial segment of Amazon’s Supply Chain is its logistics and delivery teams. Amazon ships products mainly via two channels – road and air.  Amazon maintains a huge fleet of trucks, bikes, and vans for transporting products via roads. It has also partnered with various delivery services including FedEx and UPS.

Amazon also has a cargo airline of its own called Amazon Air which is used for transporting products. Amazon Air makes more than 160 flights every day with more than 85 planes, which include 11 Boeing Jets.

This is how Amazon can meet and many times exceed its customer’s expectations in terms of fulfillment and timely delivery of their orders!

Take Away

A Supply Chain Management System is an area that can either make or break a business. If you are interested in making an impact on a business by becoming a part of its supply chain decision-making, you must get a supply chain analytics certification today!

Want to know more about the supply chain management career options? Contact us through chat support or visit our nearest training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, 

Learning Hadoop Online – Your Guide To Building A Career In Big Data

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Learning Hadoop Online – Your Guide To Building A Career In Big Data

Big data is in demand because it has the potential to change the way we live and work. It can also help businesses solve problems faster, make better decisions, and deliver better customer experiences. 

At a projected CAGR of 13.4% over the forecast period, the global big data analytics market can increase from $271.83 billion in 2022 to $655.53 billion in 2029. With this growth also comes an increased need for professionals who understand how big data works and how organizations across all industries can use it.

What is big data?

Big data is a term used to describe the collection, storage, and analysis of large amounts of data. Data collection volume is increasing exponentially. The size of the data gets measured in terabytes. Big Data technologies have been around for years, but recently they have become viable tools for decision-making in business and government. 

Why is it in demand?

Hadoop and Bigdata are a buzzword. The term “big data” has been around for a while, but it’s only recently that businesses have used this phrase in their marketing materials and press releases. As more companies begin using big data analytics, it’s essential to understand what exactly you’re getting yourself into when you decide to go down this path of working with Hadoop—and what career opportunities exist there!

Hadoop allows users access to large datasets by processing them through various methods (e.g., MapReduce). There are many benefits associated with using Hadoop: they can get used across multiple industries, including finance, retailing, and healthcare; they allow organizations access to real-time insights into their customers’ buying habits; they provide improved operational efficiency through reduced costs on hardware infrastructure maintenance over time.

Role of the Hadoop developer.

A Hadoop developer is a person who has a strong knowledge of the Hadoop platform and can design and develop applications on it. They can be an analyst, software engineer, or data scientist.

The primary role of a Hadoop developer is to work with different tools and technologies to develop big data solutions using MapReduce functions, Pig scripts, and Hive queries. They also help manage storage requirements by using HDFS, which stores large amounts of data locally within clusters without downtime due to network issues.

Why do you need Hadoop online training and certification?

It is an open-source software framework for storing and processing big data. It has become a core technology for many companies, including Facebook, Yahoo, and Amazon. The tool has emerged as one of the most popular technologies in big data analytics over the years because it can efficiently process vast amounts of data. 

Discover a career in data analytics with Imarticus Learning

With this machine learning course, the student can learn data analytics and receive job offers. Learn machine learning using data science that produces vital business forecasts and insights by applying your new knowledge to practical use.

Course Benefits for Students:

  • The most widely used data science tools and methodologies, as well as data analytics and the fundamentals of machine learning, will be familiar to students.
  • To receive a data analytics certification course, students must complete 25 real-world projects and case studies directed by business partners. 
  • Using a data analytics tool to display data is one of the most in-demand skills in the market. Therefore, recent graduates and those starting their careers might want to think about enrolling.

 Contact us through the chat support system, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

The Growth of Derivatives Markets in Emerging Economies

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The Growth of Derivatives Markets in Emerging Economies

Derivatives markets have been around since the beginning of time, becoming increasingly important as financial markets have evolved. However, derivatives are not just for large corporations; individuals can also use them to hedge against risk in their personal lives. 

This guide explores the evolution of derivatives markets in emerging economies, how that growth has affected financial systems there—and how this could change as more countries develop these markets!

Using derivatives in Emerging Markets.

Derivatives turnover has increased more quickly in emerging markets than in developed nations. Foreign exchange derivatives get the most frequently traded of all risk categories due to frequent currency turnover in emerging market currencies and an increasing share of cross-border transactions. 

The offshore trading of many emerging market currency derivatives has increased along with the global reach of emerging Asia’s financial centers. Trade, economic activity, and per capita income positively correlate with growth in derivatives turnover.

Derivatives are financial instruments generally based on other assets’ values. Derivatives can use for several purposes, including hedging risk or speculation. Most derivatives manage risk and reduce exposure to market movements by transferring it from one asset class to another.

The evolution of derivatives markets in emerging economies.

Derivatives markets are a significant part of financial systems in emerging economies, where the growth of derivatives gets driven by the need to hedge against risk. The evolution of derivatives markets in emerging economies can track back to the late 1980s when central banks began using them to manage domestic inflation and currency exchange rates. 

Impact of Derivatives Markets on Financial Systems.

The derivatives market has a positive impact on financial systems. Derivatives markets help in managing risk and make the financial system more efficient. They also provide liquidity to the market and help in price discovery.

The derivatives markets’ internationalization is driven by technological advances that have made it easier for investors to access information about global markets and regional integration through free trade agreements (FTAs). These two factors have resulted in a significant increase in cross-border trading activity over time.

Benefits of derivatives markets in EM

Derivatives markets are a great way to reduce risk and provide liquidity and transparency. This can help you manage interest rates, currency, commodity, and equity risks. It also reduces volatility in the market as well as helps manage credit/inflation risks.

The derivatives market has increased in emerging economies, with various benefits for investors. The benefits are not limited to the financial system or even the economy but extend into multiple sectors of society.

Learn investment banking courses with Imarticus Learning

With the help of the Certified Investment Banking Operations Professional program, students can begin a career in the financial markets. Students who complete this investment banking certification course will have the skills and knowledge necessary to succeed in banking, treasury, and clearing services at all stages of production. The investment banking course syllabus covers financing, strategic planning, financial management, and the valuation of investment prospects.

Course Benefits for Learners:

  • Students will gain knowledge of financial services, including managing complex securities and derivative products and their trade-life cycles. 
  • Students will get the assistance they need to start their careers in investment banking.
  • Students who complete the derivative markets training program and money market course will receive an industry-recognized certificate.

Contact us through chat support, or drive to one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Understanding fintech in the cloud computing spectrum

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Fintech has been on the rise as a significant player in the financial sector in recent years. As we continue to see a shift towards digital solutions and away from traditional financial institutions, it’s essential to understand Fintech and how it operates within the larger landscape of cloud computing. 

In this blog, we will explore the world of Fintech and how it relates to cloud computing. We will look at the most popular fintech applications and see how they use the cloud to power their businesses. 

An overview of Fintech

 Fintech is a broad term that covers a wide range of financial technologies. These can include mobile payments and digital wallets to investment management and blockchain. If a financial service or product you can deliver digitally, it can be considered Fintech.

Fintech is growing for many reasons:

There is a growing demand for digital financial services. More and more people are using their smartphones and computers to manage their finances, and they are looking for convenient, user-friendly solutions.

Traditional financial institutions are starting to embrace Fintech. Banks and other financial companies invest in fintech startups, partner with fintech companies, and launch their fintech products.

The rise of mobile devices and digital platforms has made it easier for fintech companies to reach consumers and businesses. Fintech is also benefiting from the growth of cloud computing. Cloud-based solutions are often more scalable and flexible than on-premises software, a significant advantage for fintech companies that constantly innovate and expand their offerings.

How Is Fintech Related to Cloud Computing?

Fintech relies heavily on cloud computing. Most popular fintech applications would not be possible without the cloud. 

Here are a few examples:

  • Online banking: Customers can access their accounts from anywhere globally with an internet connection. It would not be possible without the cloud.
  • Trading platforms: Stock traders need to quickly access their portfolios and place trades. The cloud enables this by providing the necessary infrastructure.
  • Payment Processors: Fintech companies use the cloud to process payments.

The cloud provides the flexibility and scalability that fintech companies need to grow and scale quickly.

Discover Career in Fintech with Imarticus Learning

The Professional Fintech Certification is the first of its kind online FinTech course, providing extensive knowledge of all elements of FinTech and comprehensive, strategic, and hands-on training with several technologies, including API, Blockchain, Cloud Computing, AI, Machine Learning, IoT, and RPA.

Course Benefits for Learners:

  • Financial technology courses will educate students on applying machine learning algorithms and blockchain technology to their business needs, ensuring that they are well-equipped!
  • The future of Fintech is bright, and learners can stay up to date on the newest advances by attending networking events, job boards, or webinars.
  • With this fantastic new resource, students will have access to some helpful tools that can assist them in finding their dream job after graduation!

Machine Learning A-Z: Hands-on Python and R in Data science

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R and Python are both equally great programming languages. However, each has its own set of advantages that it offers to the user. For example, when we are talking about development processes or IT operations, Python is always a better option. But when it comes to statistical tasks or analytics, R can prove to be a much more suitable alternative.

This is because R has been created for Statisticians and for statistical projects. Skilled programmers can, however, employ any of the two languages to perform any task. For instance, Python can be used for using statistical techniques like Regression Analysis or Bayesian inference on datasets. Similarly, R can also be used for building new Data Science tools and data models. 

Python is quite easy to learn with simple syntax while R has various language boundaries. One can easily learn Python online with the help of a course. However, R is far superior in graphical and statistical procedures. R is more scientific in nature and will be much easier for statisticians or professionals who have worked with MATLAB, another scientific programming language.

Python is more focused on running algorithms and makes it easy to build programs in general. In Data Science, however, both are equally important and competent languages. R and Python can work with massive databases and are equally good at Machine Learning projects. 

R in Data Science

R is used in Data Science for graphical and statistical purposes. This language can help users create advanced visualizations and high-quality graphics as well as dynamic graphics. R is also great for data mining and statistical computing in general.

R has a set of functions that allows datasets to be loaded into the memory with program statements, but that is only required if you are going to be building R programs that will keep getting used for various functions. Otherwise, you can simply use the data import function in R Studio (IDE for R). R is able to work with data in two different formats in R studio, CSV and TXT. Once you select the dataset you wish to be working with, R will load the dataset and you can then work on it.

Python in Data Science

Python is a high-level programming level that does not require compilation before running code. This makes it very fast to use for all kinds of projects, including Data Science and Data Analytics. Python is extremely flexible and is a multi-paradigm language, thus, allowing Data Scientists to use different approaches and keep improvising the language with extensions and plugins.

Before loading a dataset in Python, you must first import pandas (library) and install them in Python. After that, a custom function must be created that loads the dataset for you. By creating a load_csv function, you can fundamentally provide an argument for your dataset’s file path.

Also, the readlines() are used in order to ensure that the program returns a list containing the lines inside the .csv dataset. You can also additionally present the data in a more visually appealing way by returning the dataset in a data frame format. This makes it easier to view the data as compared to the native list format or NumPy arrays.

Conclusion

Both the languages also are open-source and have huge communities behind them to keep providing new libraries. There are also a good number of updated tools and powerful IDEs (Integrated Development Environments) available for both R and Python.

If you wish to learn Python or R for Data Science, you should definitely opt for a solid Post Graduate Program in Data Science. You can also choose to take up a Machine Learning course with a placement or a Data Analytics course with placement as well. 

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