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Category: Analytics

Which Is the Best Artificial Intelligence Course of 2021?

Posted on by Imarticus Learning

In today’s technological era, machines are everyday partners of humans. Artificial Intelligence (AI) has a crucial role in determining the intelligence of machines.

In 2021, many businesses and public services rely on AI for day-to-day operations. College graduates and young enthusiasts are learning AI to build a successful career. There are many AI courses in the market and, it can get difficult to choose one. Read on to know the best AI course of 2021 and why one should learn AI.

Why learn artificial intelligence?

 The reasons one should look for an artificial intelligence course are as follows:

  • Many organizations and businesses are adopting an AI strategy. The rise of automation in the industry processes has fuelled the demand for AI experts. By opting for an artificial intelligence course, you can future-proof your career.
  • Since AI is a new-age technology, there is a shortage of expert individuals in the industry. An AI professional earns a handsome salary and will always be in demand.
  • Gone are the days when AI was only used by robotics and the space industry. Nowadays, AI has become a versatile technology that is used by numerous industries. Some popular sectors that use AI are healthcare, logistics, finance, banking, and legal sectors. You will open multiple future career prospects for yourself by learning AI.

Why go for online training?

Educational institutions usually do not provide certification courses to students. They offer a complete degree program in which AI is just one of many subjects. If you are willing to only study AI, you would have to go through the whole degree program. It is where online training is a boom for AI enthusiasts.

Also, the recent pandemic (COVID-19) led to the suspension of classroom lectures. Online training has helped AI students during the pandemic period. Working professionals can also commit to an online program easily while continuing their job. However, you need to choose industry-oriented AI ML courses that make you job-ready. Imarticus Learning is a reputed EdTech platform that offers AI ML courses with an industry-oriented curriculum.

 Why choose the AI/ML course of Imarticus Learning?

Imarticus provides a Certification in Artificial Intelligence & Machine Learning that is 9-month long. In association with IIT Guwahati, this AI/ML course is a blessing for AI enthusiasts amidst the pandemic. Besides this certification program, Imarticus offers many other artificial intelligence and machine learning courses like PG Program in Data Analytics & ML. The reasons one should choose the certification program in AI/ML from Imarticus are as follows:
artificial intelligence and machine learning courses

  • This course is offered in association with one of the most premier institutes in India i.e., IIT Guwahati. You will get to learn from academic professors and industry experts.
  • Imarticus strictly follows an industry-oriented curriculum that makes you learn job-relevant skills for the AI/ML industry. During the certification course, you will work on 25 real-life industry projects that will make you job-ready.
  • Some of the top languages and tools covered in this certification course are NumPy, TensorFlow, OpenCV, Spyder, Pandas, and Jupyterhub.
  • Imarticus also offers career services at the end of the certification course. Professionals trained by Imarticus in the past work in some of the top organizations of the globe like Accenture, Standard Chartered, Oracle, Deloitte, KPMG, Infosys, and Tata.
  • This course will also offer a 3-day campus immersion program where you can interact with the peers and faculty members of IIT Guwahati.

In a nutshell

Imarticus provides some of the best artificial intelligence and machine learning courses in India at affordable rates. You can also get a scholarship of up to 40% for the certification course in AI/ML offered by Imarticus. Start your online artificial intelligence course now!

Why is a Supply Chain Certification Lucrative in the next 10 years?

Posted on by Imarticus Learning

Supply Chain Management (SCM) oversees the manufacturing of a product from its origin until it reaches the consumer. Although it may sound simple, it involves several processes and thus requires a set of skilled professionals to ensure its smooth functioning. It is such an essential job profile that people are rushing to find an ideal Supply Chain Management course to become qualified.

Not only is it popular these days, but its prospects also don’t seem to dim in the next 10 years. Could these be the reasons why the supply chain management career is going to be lucrative in the near future as well? Let’s find out!

It offers diverse job opportunities

The SCM career options are so vast that it is difficult to find which one would be the best. These days, every product in the market would have undergone countless planning processes, material procurement, assembly, production, inventory management, and many more steps. Each of these areas comes under the SCM and will need professionals with special skills. It also involves almost every industry in one way or the other, so the diversity of job opportunities is numerous.

Ideal for skill development

supply chain management courses

Skill development is trendy these days. A supply chain management career opens up the opportunity to brush up on several skills. These skills include management, interpersonal skills, communication, teamwork, networking, etc. They apply to all industries, so it is a great way of formulating a wonderful portfolio of both professional and personal skills. Sometimes it can be more productive in skill development than the leading supply chain management certificate course online.

Suitable for all

This is a wonderful career without the hassles of a corporate ladder where everyone is pressured to reach the top. A career here will let you enjoy success and give satisfaction with the prosperity of the company as well. There are opportunities for both management and executive roles and you can still reach the top positions.

Compatible with the technologies

A supply chain is a global industry that is now involved with the latest technologies as well. AI, predictive analysis, automatic cars, drones, etc., all can combine with the supply chain to make each industry successful. This will force people to be more adept at analytical and management skills with an awareness of the overall end-to-end happenings in this field.

Finding the best Supply Chain Management Course

There are plenty of supply chain management certification courses available online. But what makes the Professional Certification In Supply Chain Management & Analytics course in collaboration with the IIT Roorkee different is its hands-on learning process dealing with real-life SCM projects.

supply chain management courses Other than being a top course endorsed by an IIT, this allows the aspirants to become better at decision making. It also permits an in-campus interaction with other students and faculty.

By solving real-life industry problems, it helps in creating a personalized portfolio to impress companies. On top of that, the analytics help in combining the SCM with data and generate a few techniques to make data-centric decisions.

The best course should have a sparkling curriculum that has every step involved in the management from designing to the sales operation. The course could last anywhere from a few weeks to one year. The salary prospects after the completion of the course could be in the range of 3.5-20 LPA, depending upon the qualification, skills, and experience.

Conclusion

People often have different interests in their career and SCM is a fantastic option that can open up opportunities in almost every field. They can have a different career but could still be within the supply chain.

Why is IIT Supply Chain Management Program the Best?

Posted on by Imarticus Learning

The supply chain encompasses all of the actions, people, organizations, information, and resources required to transport a product from conception to client. In the consumer goods industry, this is likely to include raw materials, production, packaging, shipping, warehousing, delivery, and retailing. The end goal is straightforward: fulfill the customer’s desire.

Further, a supply chain management course is the process of combining supply and managing demand not only within the firm but also across all of the supply chain’s innumerable units and channels so that they function together quickly and productively.

Supply chain management is critical for any firm since it can introduce various benefits. But, inadequate supply chain management can result in very expensive delays, quality concerns, or reputation issues. Poor supply chain management can also lead to legal concerns in some circumstances if vendors or processes are not compliant.

Technology advancements have opened enormous possibilities for supply chain management, allowing supply chain managers to collaborate intimately and in real-time with supply chain participants.

A certified supply chain analyst has a very important role in every industry that involves the supply chain. A supply chain management career can guarantee you a high-salary job in various sectors. The IIT Supply Chain Program is the best and comes with some exclusive benefits.

This 6-month supply chain management online course has been specially prepared by IIT faculty and industry professionals to assist you in learning. With the ever-increasing trend of e-commerce, the number of products in transit has also increased. The number of supply chain management employees has increased disproportionately across industries. This training will prepare you to capitalize on this opportunity.

Why Pursue IIT Supply Chain Management Course?

The benefits of IIT certified supply chain analyst course are as follows:

  1. Discover supply chain management knowledge and much-required analytical skills with this program built by IIT Roorkee’s DoMS & E-Learning Centre. This course will assist you to become more data-centric and improve supply chain selection by using the strength of Python.
  2. This supply chain management online course will assist you to learn from one of India’s greatest faculties via live online sessions and conversations. IIT faculty workshops will help you construct essential concepts in SCM, while industry specialists will provide hands-on learning for SCM processes, tools, and strategies. This course will teach you how to construct a solid SCM foundation and use analytics through engaging live sessions with renowned trainers and industry professionals.
  3. Participate in a three-day campus immersion session to tour the IIT Roorkee campus. During the campus immersion, you will connect with your peers and learn from IIT academics. You will get the opportunity to go to the Delhi or Noida campus and work on the Capstone Project with the help of expert mentors.supply chain management courses
  4. Tackle tough real-world challenges that necessitate a full understanding of principles, mastery of skills, and comprehension of the business context. With these real-world SCM projects, you can boost your resume and stand out. You will be able to create your own project portfolio and dazzle potential employers. Through rigorous in-class exercises and SCM projects, industry experts teach you crucial job-relevant skills.
  5. Massive volumes of data are generated by supply chains – Big Data, to be more explicit. Prepare to participate in the creation of smarter, more strategic, and tactical global supply chains of the future by merging traditional supply chain methodologies with data-driven judgment.

It is very evident that the demand for a certified supply chain analyst is increasing by the day. In such a situation, certification can give your career the right boost and help you bag your dream job in your desired company. Enrolling in this course can be a game-changer for you!

How Is a Machine Learning Course Helping Secure Bright Careers?

Posted on by Imarticus Learning

Machine Learning (ML) is an emerging technology that has taken businesses by storm. Currently, more than 30% of businesses in India have already adopted machine learning technology or are planning to adopt it. Besides being termed as the ‘hottest job of the century’, ML job roles also offer lucrative salaries.

ML along with AI (Artificial Intelligence), plays a crucial role in data science operations. Young enthusiasts are looking for ML/AI courses that offer them industry-oriented learning. Read on to know how an ML course can aid in building a successful career.

Reasons to learn ML & AI

 The reasons one should look for an industry-oriented ML course are as follows:

  • The compound annual growth rate of the global ML market is more than 40%. Businesses are adopting ML/AI technologies on a large scale. There will be no shortage of ML job roles in the industry for the coming years. Also, the salaries of ML job roles in the industry are expected to increase in the coming years.
  • ML and AI are versatile technologies that are used by different sectors of the industry. ML/AI algorithms are also used for day-to-day operations in many public sectors. Sectors like healthcare, logistics, e-commerce, education, and retail use ML for their day-to-day operations.
  • Machine learning helps in building smart data analysis algorithms. You can gain meaningful insights from data analysis and understand your customers/clients better. Data analysis skills will also come in handy for making several real-life decisions.

Why go for online ML training?

Colleges in India usually do not provide a certification course in AI or ML. AI/ML is usually included in the traditional degree programs as a subject. You will have to go through the entire degree program to learn machine learning at a college. It is where online training allows you to learn machine learning without enrolling in a degree program. Also, the recent COVID pandemic made it difficult for young enthusiasts to attend classroom lectures.

artificial intelligence and machine learning coursesWorking professionals can commit to an online machine learning course depending upon their free hours. However, you will have to choose an effective machine learning course that makes you job-ready. Imarticus Learning is a reliable EdTech firm that offers industry-oriented machine learning and artificial intelligence course.

Why choose the ML course offered by Imarticus?

Imarticus Learning is a reputed EdTech platform that offers a Certification in Artificial Intelligence and Machine Learning in partnership with IIT Guwahati. This 9-months long certification program can help in preparing for numerous jobs like ML/AI engineer, data analyst, and data scientist. The reasons one should choose the AI/ML certification course are as follows:

  • ai and ml courses
    At the end of the course, you will receive a certificate endorsed by ITT Guwahati, one of the top educational institutions in India. The AI/ML certificate endorsed by IIT Guwahati will be globally recognizable. Also, you will get a 3-day campus immersion program with this course that allows you to interact with faculty members and peers of IIT Guwahati.
  • You will work on more than 100 assignments and 25 projects during the course. Real-life projects will aid in learning the ML industry practices.
  • Numerous AI/ML topics will be covered in this certification course. Some popular topics covered in this course are dimensionality reduction, unsupervised learning, deep learning, NLP, etc.
  • Towards the end of the machine learning and artificial intelligence course, you will compete in a hackathon to judge your AI/ML skills. You will also receive career support towards the end of the course from Imarticus.

In a nutshell

Imarticus has already placed many data scientists in some of the top organizations of the world. With their industry-oriented course curriculum, they will make you job-ready. Start your ML certification course now!

How Data Analytics is Reviving Up the Digital Economy

Posted on by Imarticus Learning

Today, data analytics is a booming industry. It has been estimated that the data analytics market will grow to $187 billion by 2025. These numbers are staggering and they just show how much potential this industry holds for those willing to take on it as a career.

Data analysts have an essential role in our digital economy because they dig out insights from raw data to help companies make better decisions. To succeed as a data analyst, one must be adept with programming languages such as Python, R, SAS, or SQL, among others, and know statistical analysis techniques.

Data analytics course is used to make decisions about important marketing campaigns, product development, and customer service. Data analysis techniques include descriptive statistics, inferential statistics, hypothesis testing, cluster analysis, exploratory data analysis (EDA), causal modeling, and regression modeling.

Use of Big Data and Analytics

The definition of “digital economy” has been blurred by its widespread use but in general, let’s understand what it means. The digital economy uses technology to create, capture, store, manage, transmit and exchange information. One example of this includes using a cell phone app to order food online.

Here, the companies have created an online interface for customers to easily find restaurants that deliver in their area and then order by clicking on what they want. This eliminates the need for human intervention because all orders are taken or placed through the device. This means that the entire process has become hassle-free.

Another most common example where big data is used is retail stores. They use it to analyze their customers’ shopping habits, so they know what products to put out on display during a particular time frame throughout the day. This helps them in maximizing profits while also making sure that every customer gets a personalized experience when they visit the store.

In the same way, most companies use big data to analyze and find patterns in the available data. They leverage this data to derive insights that offer a unique experience to their target group. Companies dig deeper into these insights to identify untapped business opportunities that they can explore. Companies can identify a niche and expand into that area to fill the need gap.

They also have many other options for growth, such as partnerships, joint ventures or acquisitions within their target industry verticals; these strategies allow them to survive and thrive in changing markets while often expanding business operations. While exploring new business areas, companies always study the data available to forecast the project’s profitability.

Use Case of Big Data and Data Analytics

Data analytics is an essential tool when it comes to modern marketing & growing the digital economy. Without it, a company’s decisions would be made without any data to back them up, and you could miss out on some excellent growth opportunities!

best data analytics courses in IndiaThe good news is that there are many different types of data analysis techniques available, so you can find one that works best with the kind of information you have at hand.

If this sounds like something worth investing in, you can consider enrolling for several online courses on Data Analytics from Imarticus Learning. You will learn how to analyze data yourself and come up with insights or use a computer program such as Microsoft Excel and several other data science tools to analyze data.

Conclusion

The digital economy is expanding day by day, and it might replace traditional economies in the future. Artificial intelligence (AI) powered tools manage data in this new environment, while manual tasks remain essential for understanding the numbers.

However, businesses rely heavily on consumer insights obtained through machine learning algorithms. These algorithms are decoded with the help of analysts who provide valuable input during the decision-making processes.

How To Build A Credit Scoring Model With Machine Learning?

Posted on by Imarticus Learning

Credit bureaus and lending institutions have embraced big data and machine learning to develop credit score models on the basis of which the creditworthiness of a borrower is judged. This has many benefits for the business as they can better assess the risks of offering loans, gauge the repayments and plan accordingly. Businesses today take advantage of the huge volumes of data proliferating nearly every sector to create their own scoring models based on Big data and a long delicate and expert process of executing a machine learning course of algorithms to build their own models.

The trends:

The era of basing decisions solely on credit scores from bureaus are over. Today custom models work better and more accurately since they use data from a number of sources both internal and external to assess creditworthiness. Such data could include supplier information, account data, customer relationship or other market data. More the data the more accurate and efficient the scoring model becomes.

How to create the scoring model:

1. Goal setting:

Clear cut goal setting is important to achieve accurate results in scoring models. The goal needs to be in mine with the needs of business and its scoring model. For example, the goal could be the probability of late repayments of existing loans and dealing with the repercussions. Or, it could be using the data to decide on scoring the financial repayment plans of borrowers and their creditworthiness.

2. Data gathering:

This is a crucial requirement as all assessment is done on the basis of data. With enough data volumes and reliable data, a scoring model is made for the specific goals set. The test model so built can be used to supervise the model which will help in training the model under supervision from domain experts. Beyond this point, you will need to test the model with credible credit score website databases like the Boostcredit101.

3. Building the model:

With both internal data and comparative data in place, the experts can now build your scoring model. The Machine Learning Course procedure is complex and involves a large number of algorithms trained to interpret the data before the final test model is ready for deployment. It goes without saying that the goals of the business owners and the aim of the model builders need to be the same and both would need to contribute to the end goals and success of the scoring model being developed.

4. Validation:

The next phase is to validate the process and ensure the scoring model provides accurate results. Most applications lean on how to predict the late payments of the debtors. The scoring model will use the new data while scoring it against the test results to produce a score between 1 and 100. Higher scores mean fewer defaults and vice versa. These scores are also repeatedly done as changes in financial status, incomes and economic growth can all affect the score.

5. The implementation:

This final phase is where the permanency of the scoring model is tested by the actual implementation. A successful model will remain while the inefficient models get wiped out. Challenger models play the role of checking to see if the scoring model is functioning well or is the challenger is the better model.
The Big Data connection:
A shift from total reliance on credit-bureau data has seen lending banks, institutions, and companies that use credible data buy such data. Data is digital gold and large volumes of big data are needed to train AI on a machine learning course.The cleaning, parsing and making sense of such large volumes of multivariate data is a job for expert data scientists. This data is then used to create the scoring model be it a new or challenger model.
According to data scientists, it is these scoring models with the best ML algorithms that ML can accurately tap all unrelated factors and relationships in the data to provide a better scoring model. Though it is not without problems it is heartening that ML can help the machines self-learn with data and the more data one inputs the better are the results of the scoring model.

Conclusions:

The insights, big data, and ML have helped create scoring models for businesses, lenders, and organizations. While traditional credit bureau reports are also crucial, ML can go further with scoring models helping them add insights and provide newer business points of view. If you are interested in learning more about ML and credit risk scoring you could do a machine learning course at the Imarticus Learning Institute where futuristic technologies are taught and skilled on. Don’t wait too long. Start today!
For more details in brief and further career counseling, you can contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Bangalore, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

Python Developer Salary And Certification Guide To Get You To The Top!

Posted on by Imarticus Learning

Python is one of the most popular and widely used programming languages across the globe. The use cases of Python have broadened from SEO and web development to AI, IoT, Fintech, machine learning, and data analytics. Today, with the support of a collection of software libraries, Python enjoys the reputation as an advanced programming language that can be used for general purposes.

Python training supports a variety of programming paradigms which makes it a user-friendly programming language that can be scaled for larger applications.

Python Certification coursePython sits at the fourth position in the TIOBE index, which tracks the popularity of computer programming languages. Diverse use cases and popularity make Python a favorite choice of many fields. This brings good compensation benefits as well.

The salary of Python programmers varies depending on the field they are working for.

Python Developer Salary

Given the diverse use cases of Python, companies are actively looking to hire Python talents. No wonder python developer tops the searches on the leading job portals. The job could vary from application developer to data scientist, web developer, or DevOps engineers.

The increasing demand for professionals is also reflecting in the compensation packages offered. The shortage of talents has pushed things in favor of the jobseekers. This is a good time to negotiate on the salary package. The average salary for different roles in India and the international job market are as follows:

Job Role Annual Salary
India International
Data Scientist ₹708,012 91,838 USD
DevOps Engineer ₹10,00,000 93,931 USD
Software Developer ₹10,00,000 118,950 USD
Senior Software Engineer ₹10,00,000 129,000 USD

 

Why You Should Learn Python Language

As discussed earlier, Python is becoming a popular programming language widely from web development, desktop apps, network servers, back-end APIs, etc. Its use case in artificial intelligence makes it an even more attractive career option today. Here are the top reasons to enroll in a Python programming certification course today.

  • Technology giants are on the lookout for Python professionals to help them develop several applications. Being the programming language used in many applications, Python skills are one of the most valued resources in these companies. The top names among the Python employers are Google, Facebook, Instagram, NASA, YouTube, Reddit, Quora, IBM, Mozilla, Dropbox, Yahoo, Uber. Getting trained in Python increases your chances to become a part of these big names.
  • There is a need gap in the job market. The need for Python professionals is increasing as it finds its application across many fields. However, there is a serious lack of talent. Python-trained professionals can get into futuristic fields as well – the likes of AI, robotics, big data analytics, and machine learning.
  • Having a certification increases your chances of getting hired. So, if you are interested in a Python Programming career, you should enroll in a Python programming certification course. Many reputed certifications train you with projects and case studies to help you deal with real-life problems.Python Certiication courses
  • Flexible syntax and a broad array of libraries make Python ideal for beginners looking to build their careers in this field. The “CodinGame 2020 Developer Survey Report” says that Python tops the preference of 10 K developers with 84 percent among them favoring it.

Python is growing very fast in terms of popularity. It is climbing up the list of popular programming languages, pushing its competitors down the list. It has successfully grabbed the second position in popular platforms like Github. It is just a matter of time for Python to secure the top position.

All these have increased the demand for Python-certified professionals. So, if you are aspiring to a Python programming career, there is no better time than this to start it.

Related Article:

https://imarticus.org/python-coding-tips-for-beginners/

What’s The Quickest Way To Learn Math For Machine Learning And Deep Learning?

Posted on by Imarticus Learning

In modern times we have everything from developments like smartphones, robots, driver-less cars, medical instruments like CAT scans and MRI machines, smart traffic lights, and a host of animated games. Even payments have gone digital and cashless! And all this has emerged over the last decade due to AI, ML, and data analytics.

The future holds great promise for development in these fields and to make a high-paid scope-filled career in any of these fields, mathematics is the key ingredient that you must learn if you want to learn machine learning. ML runs on algorithms and the algorithm is dependent on knowledge of mathematics and coding.

Why mathematics is so important in ML:

Some of the many reasons are :

  1. Selecting the apt algorithm with a mix of parameters including accuracy, model complexity, training time, number of features, number of parameters, and such.
  2. Selecting the validation of strategies and parameter-settings.
  3. Using the tradeoff of Bias-Variance in identifying under or overfitting.
  4. Estimating uncertainty and confidence intervals.

The math components required for ML:

ML algorithms require proficiency in the three topics of Linear Algebra, Probability Theory, and Multivariate Calculus.

Let us discuss the topics you need to learn machine learning under each of these heads.

A. Linear Algebra:

The use of Linear algebra notation in ML helps describe the structure of the ML algorithm and the parameters it depends on. Thus linear algebra is important in the interconnection of neural networks and their operations.

The topics that are important are : 

  • Vectors, Tensors, Scalars, Matrices,
  • Special Vectors and Matrices
  • Norms of Matrices
  • Eigenvalues and vectors

B. Multivariate Calculus:

ML learns from its experience with the data set and to supplement this we need calculus to power learning from examples, improving performance, and updating parameters of the different models.

The important topics here are : 

  • Integrals
  • Derivatives
  • Differential Operators
  • Gradients
  • Convex-Optimization

Probability Theory:

The assumptions about data use this theory to design the AI and its deep learning capabilities. The key probability distributions are crucial to algorithms.

Study these topics well.

  • Random Variables
  • Elements of Probability
  • Distributions
  • Special Random Variables
  • Variance and Expectation

Can you learn Math for ML quickly?

To learn machine learning it is not required to be an expert. Rather understand the concepts and applications of the math to ML. Doing things like math is time-consuming and laborious.

While there may be any number of resources online, Mathematics is best learned by solving problems and doing! You must undertake homework, assignments, and regular tests of your knowledge. One way of getting there quickly and easily is to do a learn machine learning course with a bootcamp for mathematics at Imarticus Learning

This will ensure the smooth transition of math and ML applications in a reputed institute for ML where they do conduct bootcamps. At the end of this course, you can build your algorithms and experiment with them in your projects. But, the main question that remains is why do a learn Machine Learning Course at Imarticus in the first place?

The Imarticus Learning course scores because: 

  • They have sufficient assignments, tests, hands-on practice, and bootcamps to help you revise and learn machine learning.
  • They use certified instructors and mentors drawn from the industry.
  • They integrate resume writing, personality development, mock interviews, and soft-skill development modules in the course.
  • They have convenient modes and timings to learn at your own pace for professionals and classroom mode for freshers and career aspirants.

Conclusion:

Mathematics is all about practice and more practice. However, it is crucial in today’s modern world where AI, ML, VR, AR, and CS rule. These sectors are where most career aspirants are seeking to make their careers, because of the ever-increasing demand for professionals and the fact that with an increase in data and the development of these core sectors, there are plentiful opportunities to land the well-paid jobs.

At the Imarticus, you can consider the Machine Learning course, you will find a variety of courses on offer for both the newbie and tech-geek wanting to go ahead in his/her career. Start today if you want to do a course in AI, ML, or Data Analytics. For more details in brief and further career counseling, you can also contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Hyderabad, Delhi, and Gurgaon.

What is the Difference Between a Business Analyst and Project Manager

Posted on by Imarticus Learning

Workspaces have evolved dynamically. This has led to the creation of different job roles and functions across industries. Different key roles have come into the picture in recent times. These roles have strategic importance in the functioning of organisations of all kinds. Also, in most cases, these new roles have now become pivotal points around which the stakeholders of a company revolve.

Project managers and business analysts are now seeing the light in different corporations. They handle some of the most important functions within and outside the organisation.

Let’s know more about their roles and responsibilities.

Who is a Business Analyst?

Business Analysts analyse and evaluate huge sets of data to come to different conclusions which can later be transformed into a business decision. A business analyst has good control over data and knows how to extract important information from a pile of Data. A Business Analyst works with the organisation and drives the changes the company goes through. These people are analytical and are good with numbers.

Role of a Business Analyst

Mentioned below are some of the roles of a Business Analyst:

  1.  Tries to understand the needs of different departments and stakeholders and serve them with what they require
  2. Uses various data modelling and handling techniques to crunch data and come with important data points
  3. Forecasts and manages risks which arise during the normal course of business.
  4. Recommend business solutions to the top management to improve the processes and outputs
  5. Formulation and implementation of strategic plans to drive growth and revenues of a company.

You can take up a business analyst course to train yourself and become a better business analyst.

Who is a Project Manager?

The job of a project manager is quite interesting. He is in charge of the different work projects which are taken up by any company. He leads an entire project and manages everything that is required to make a project successful. These activities include Planning, Strategizing, Execution, etc.

Project managers also have to become good leaders as they handle an entire team. He must also know about project management as it is an elaborate task. A good project manager should have the willingness to use innovative techniques while handling different projects.

Role of a project manager

A project manager performs the activities listed below:

  1. Guide his team throughout the different phases of project management
  2. Set up expectations and goals to be achieved by a particular project and work towards achieving those goals.
  3. Track the entire project lifecycle
  4. Develop a plan to manage the entire project
  5. Ensures the completion of a particular project within the given time frame

The difference between a Business Analyst and a Project Manager?

Though the two roles sound similar they have a huge difference when it comes to their role in the organisation. A business analyst course will help you understand how business analysts are different than project managers. A project manager takes care of a particular project.

He is responsible for running that project. He has to formulate a strategy and develop processes for the completion of the project. On the other hand, the Business Analysts analyzes different data sets to come to different conclusions. His job is to analyse different trends and draw out conclusions from these observations.

Both of these roles are very different. A project manager takes up a managerial role and manages all the aspects of the project whereas a business analyst has an analytical role where he deals with all kinds of data related to the company.

Guide To Using Advanced Analytics And AI In Business Applications!

Posted on by Imarticus Learning

AI-Possibility to Reality

The widespread advancement in the field of AI helped organizations to manage the employees and customers in a better way.

For example, the chatbots, meant to serve the purpose of handling the customer’s inquiries and complaints are a source of relief for the employees as well as customers who need not to wait for long for the response from a company. To understand the AI in businesses in detail we must familiarize ourselves with the basic terminology related to it.

Artificial Intelligence

AI is a concept which demonstrates the ability of a machine to think and execute the tasks in a smarter way as humans, using much complex logic in a single frame. Human intelligence forms the fundamental basis to facilitate the design of an AI. The different abilities of humans such as perceiving, reasoning, problem-solving, etc. use analytical skills. A machine when trained to use these skills can work with accuracy and no fatigue.

AI Augmentation

The way the human brain is trained using different stimuli, AI is also trained using historic data. To understand in detail, what happens to the historic data, we must understand different analytics from business perspective. Descriptive Analytics (What happened?) (maximum manual intervention), Diagnostic Analytics (Why did it happen?)(Significant manual intervention), Predictive Analytics (What could happen?)(Correcting the mistakes manually), Prescriptive Analytics (What should we do?), Cognitive Analytics (Cause something to happen)(Fully automated)

Moving beyond these analytics, advanced analytics helps to add knowledge and gives a progressive nature to the AI to make decisions in a holistic way.

Big Data

To train the AI to work in a specific field Big data plays very important role. Big Data is described by the 5 V model.

  1. Volume-describes the big size of the data
  2. Velocity-describes the speed at which the data is created, basically the mathematical ratio of quantity and duration of data creation.
  3. Variety-describes the various heads under which data is created
  4. Veracity-describes the accuracy of the data, in other words, it tells if the data is reliable or not.
  5. Value-Transferable nature of data in the useful form

Machine learning and predictive analytics

Technically Machine learning and predictive analytics share similar fundamental structures of complex algorithms with the same objectives of forecasting. The underlying difference between the two is the amount of data involved and human intervention.

Predictive analytics make use of different sets of algorithms to evaluate the viability of the results. It means, because of its probabilistic nature it helps in forecasting the problems along with the prediction of the possible solutions to the problems. One of the applications of Big Data lies in the Fin-tech industry, which helps the organizations to predict if the future bad debt. To get such predictions, it is very important to train the AI with a large amount of data.

On the other hand, in Machine learning, one cannot observe the evolving nature of the data and system adaptations with the new data. ML just focuses on data availability and forecast.

In predictive analytics, human intervention is required to train the AI, but this is not the case of ML.

Methods and techniques for getting the best out of given data

Advanced statistical and Mathematical techniques such as Bayesian theory, Probability distributions, Normal curves, etc. help to extract best out of a given set of data by defining the unique algorithms in coherence with the human expertise and experience. Such algorithms help in the automation of the quality and optimized decision making in business, which in turn results in more focus on profit-making.