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Category: Analytics

Role of social media in a supply chain analytics course

Posted on by Imarticus Learning

With the boom in technology, companies encourage their employees to embrace and actively participate in social media platforms. The vigilant and active social media approach helps the companies expand their online reach and identify and tap new revenue sources. 

The Supply chain analytics certification, in addition to the activeness of employees on social media, helps to build active brand awareness.

Over time, the logistic arena has embraced social media in the supply chain tactics. Although widespread adoption of social media in the supply chain is unlikely to occur overnight, a gradual adoption over time appears to be the safe bet.

Social media could dramatically transform the industry’s procedures. Supply chain management professionals are currently keeping a close eye on what’s going on in social media and preparing themselves as best they can for future developments.

The SCM course at Imarticus prepares you to become supply chain analyst.

How Social Media is Useful in Supply Chain

We cannot deny that social media is all about forming connections and utilizing them throughout the supply chain. When the supply chain partners use social media, they get insight into a variety of supply chain, industry, and competition challenges. It also helps establish partnerships and identify critical performance indicators, such as a carrier’s on-time performance or slow shipper payments. Some business entities also use social media to gather feedback from their clients and improve suggestions.

Supply chain participants can also use social media to keep track of supply chain events and transactions, such as a delivery delay or a carrier failure to pick up a shipment, and keep everyone informed about current happenings. Companies may know about a shipment’s arrival or departure from a particular warehouse through Twitter messages. Twitter can announce the demand for specific loads or notify drivers about accidents or road closures. Social media also helps companies get more timely and meaningful information about risks and occurrences, allowing them to take remedial action faster and reduce the impact of a supply chain interruption.

It is a valuable tool for supply chain professionals to find innovations, evaluate commodity and pricing trends, capture best practices, and engage with clients, colleagues, and suppliers, social media. It can improve existing processes, reduce risk, and boost efficiency. Businesses may promote supply chain innovation by leveraging the pooled ideas and knowledge of supply chain players, which leads to continual improvement and commercial growth.

Supply chain management is about finding the most efficient means to convey information to the ultimate users. Inevitably, social media aids in disseminating critical information and continues to be an effective and successful means for businesses to communicate that information quickly. Companies that disregard social media miss these prospects and potential commercial growth.

Do you want to utilize social media in your IIT supply chain management operations? For this, you should thoroughly evaluate both its benefits and the implications.

We at Imarticus, through the SCM program, teach you to improve supply chain management utilizing social media. It can improve visibility, communication, control, and minimize operational and personnel expenses. With a more efficient and reliable supply chain, you can have improved customer satisfaction. The benefits of adopting social media to better supply chain management do wonders for your organization, and you will feel these benefits throughout your entire firm.

Here’s why you should choose supply chain planning as a career

Posted on by Imarticus Learning

IIT supply chain management manages supply chain activities to optimize customer value and gain a last competitive advantage. Supply chain organizations deliberately attempt to construct and run supply chains most effectively and efficiently feasible. Product development, sourcing, production, and logistics are all covered by supply chain operations, as are the information systems required to coordinate them.

The supply chain analytics certification at Imarticus covers the following points:

  • The first is that almost every product that reaches a customer results from a collaboration between several firms. The supply chain refers to all of these businesses working together.
  • The second point is that, even though supply chains have been there for a long time, most businesses have solely focused on what happens within their “four walls.” Few companies comprehended, let alone managed, the complete chain of events that led to the final delivery of products to the client. As a result, supply chains have become disconnected and inefficient.
  • Further, the organizations connect with physical flows or information flows.

A physical flow transforms, transit, and storage of items and materials. They are the supply chain’s most visible component as the flow of information is crucial for every organization.

Information flows are essential for every organization as it governs the day-to-day flow of goods and materials moving around the supply chain.  The SCM program at Imarticus helps develop the strategy to take care of the needs and requirements of the customers.

How to Become a Supply Chain Analyst

Data collection is essential for working in any organization, but management and handling of data to be helpful in the organization is even more crucial. You can have a promising career in supply chain analytics.

So, what does supply chain analytics do? A supply chain analyst examines the flow of goods through a distribution system. The analyst looks for flaws in the current process and then works to find solutions to enhance it, ultimately boosting supply chain performance.

Further, analysts are essential at every level of the supply chain management process, including obtaining data, interpreting data, communicating with supervisors, peers, and subordinates, and facilitating decision-making.

Stages of Supply Chain Management

Every stage of supply chain management requires analysts. Analysts are critical in every aspect of the supply chain, from material procurement to network architecture and all in between. Here are some supply chain management stages (areas) to consider:

  • Raw material sourcing
  • Production planning
  • Inventory management
  • Demand planning
  • Distribution planning
  • Network design

Career Options at Supply Chain Management

Supply chain management is a lucrative career opportunity. By opting for SCM course at Imarticus, you have the following career options:

  • Sourcing analyst
  • Material analyst or material planner
  • Production analyst
  • Inventory analyst
  • Demand planning analyst
  • Deployment analyst
  • Transportation analyst
  • Supply chain modeling analyst

Data analysis using SQL – All you need to know

Posted on by Imarticus Learning

SQL, the programming language, is the best companion for data analysts. SQL means Structured Query Language, which helps companies to build tools that can easily garner data from their databases. 

This is a valuable tool to analyze the data and make appropriate decisions based on them. Since data analysis is crucial for finding the trends and predicting them for the long-term benefits of the institutions. So data analysis using SQL is significant to get quality data from the database. 

What is SQL for Data Analysis?

A data analyst can easily access the data using SQL and read or manipulate them as needed. It is further used for analyzing the selected and stored data to get the right insights that will be beneficial for the business. 

SQL uses some basic techniques involved with it for achieving these said tasks. It also has a set of five commands to control, manipulate and analyze the data. 

Those having a basic degree or certificate such as the Post Graduate Program in Data Analytics can easily follow the instructions or handle this program comfortably. 

  • SQL is used for scripting Data Integration Scripts and is a widely used tool by Database Administrators. 
  •  It is used for handling analytical queries to get insights.  
  •  It is useful for the modification of data like deletion, insertion, or updating of the databases.  

How beneficial is SQL for Data Analysis?

SQL is a data management language that stores data in a table format. It is easy to find data and build custom models for the business. The data management here is precise and shows optimum results. 

SQL is ideal not only for data storage, it can also process, retrieve, and analyze the data as well as get insights from it, no matter how complex it is. The main reasons why SQL is beneficial for data analysis are,

  • SQL for data analysis is a user-friendly language and is quite easy to learn or understand.
  • It can efficiently process and retrieve from any of the various databases associated with it. 
  • SQL follows the standard documentation so that users can handle it well.
  • It is a widely used tool.
  • It’s useful for testing and manipulation of the data as well.
  • You don’t need any coding experience to handle SQL
  • It is completely portable and usable across all devices. 

Limitations of SQL for Data Analysis

SQL is not without errors, it has its own set of limitations.

  • The lack of a user interface often makes it challenging when dealing with larger size of databases.
  • It is difficult to do complex statistical analysis.
  • SQL will be inadequate for handling unstructured data as it requires the data to be in table format and that from the column format will not be compatible.
  • There are certain versions of SQL that are inaccessible for many users as they are expensive. 

Where to learn SQL Programming?

There are several online courses available for both freshers and working professionals to excel at this programming language. One of the best courses is the Post Graduate Program in Data Analytics & Machine Learning at Imarticus. This course is available separately for freshers and professionals to suit their schedules. The classes will be conducted on weekdays or weekends as per choice. 

The curriculum will be different according to the chosen program. The learning process includes multiple in-class projects from the real world so that the candidates are industry ready for the jobs. There will also be preparation workshops, personalized mentoring, and mock interviews. 

What learning supply chain management at the IITs is like (share like an experience)

Posted on by Imarticus Learning

As a student of commerce, Supply chain management seems like a prospective career choice because of how lucrative the job role is in the market. Initially, as a rookie student with an interest in this field, I was more drawn towards this sector because of how in-demand this job role is. To elaborate, expert professionals in the supply chain sector are mainly involved in the management of the entire production flow of goods and services, between locations and businesses. It is also inclusive of the storage and movement of raw materials, inventory, and even finished goods. 

To make it big in Supply Chain Management, a background or a qualification in this field is a mandate. Students with commerce backgrounds are open to choosing any specialization or field they want after graduation or finishing higher studies. A professional six-month program in Supply Chain Management from IIT has indeed been a life-changing course. As expected from a top-tier premier institute like IIT, it is truly the best that one can go for if they want to make it big in this industry. 

Key Highlights of This Course

Needless to say, the very mention of IIT in your CV is bound to give your career a boost amongst the numerous candidates who apply for the same job role you are aiming for. Speaking from experience, it is an advantage over other potential candidates in this field. Down below is a list of some of the reasons why taking up this course has been one of the best decisions: –

Premium Faculty

As far as personal experience goes, studying a course in IIT has been more than an honor. It has lived up to every expectation because of the premium faculties in Supply Chain Management. One to one session with expert IIT faculty has indeed helped grasp the key concepts that are a mandate in this field.

Exclusively Designed by Professionals

This 6-months program is professionally designed by industry experts and IIT faculty for students to learn. Job roles involving e-commerce are increasing day by day because of the increasing amount of movement of goods and services. This has led to an increase in demand for supply chain management professionals. With the number of job roles that have increased for Supply Chain Management worldwide, it has indeed made it better for students with this certification. With more opportunities in the market, nailing a job has become much easier thanks to the IIT affiliation as well. 

Gaining Experience Through Learning

This course is designed to make you solve real-industry problems that will give you a simulation of working in the field itself. This experience is extremely helpful in understanding crucial concepts, developing skillsets that prove beneficial for professionals in this field, and even having a thorough grasp of business contexts as well. 

Campus Immersion 

You can participate in the three-day campus Immersion module to visit the IIT Roorkee campus. You can interact with peers and learn from the IIT faculty during the campus immersion. Visit the Delhi or Noida campus and work on the Capstone Project under the esteemed guidance of professional mentors.

Big Data and Analytics Knowledge

Supply chains are hubs of massive datasets making them a part of Big Data. This course had helped not only in training traditional techniques of Supply Chain management but has even implemented a data-centric approach to SCM-related decision-making.

Conclusion

Being fresh alumni of this elite supply chain and analytics management course is bound to take your supply chain career to heights you’ve never imagined. Enroll in the from Imarticus.

How AI courses are empowering Influencer Marketing?

Posted on by Imarticus Learning

The AI certification is more relatable to the industries such as security, e-commerce, surveillance, etc. People don’t usually think of it in terms of marketing, especially influencer marketing. But it is one of the most effective strategies to promote a product. 

Influencers are the big thing these days in marketing. People tend to follow and believe them and try to implement the tips and tricks by these experts in their lives. Brands are looking for those successful influencers to market their products in their relevant industries and niches. 

There may not be a wider range of customers with influencer marketing but the small number of them could turn out to be more loyal and make a strong base. This is why it is essential to find successful influencers in the respective niches. Artificial Intelligence can help in this search for influencers and save them time and effort. 

How do AI courses help?

For the successful application of AI in influencer marketing, one must know how it works in this industry. Those who pursue any kind of Artificial intelligence and Machine Learning course must be doing a project at the end of their course. Courses such as the AIML from Imarticus offer this opportunity by options of projections from various industries, including marketing and social media marketing. 

To find the most suitable customers for any [rduct, one must find out who is interested, what their age groups and other minute factors. What helps with this finding is ML and the model projected by it. It helps narrow down the target and then goes and finds the best influencers in this field. 

An example of one such project with Imarticus certification course is Marketing Classification that finds out about the interests of teenagers to help with product marketing. Someone having experience in such a task can help find the right targets and market the products better. 

What is the result?

The result of using AI, Machine learning, NLP and other tools here will 

  • Help create a framework that helps reach the target audience
  • Identify those microblogging content creators for each marketing segment
  • Can identify the influencers who are willing to be on board for a long term
  • Helps create a constant digital presence with minimal expense 
  • Create a workflow plan to make the process easier.

Choosing the right course

Artificial Intelligence is applied in almost all industries. Each industry will be using it for the various departments and each department will be using it for different purposes. AI is not a single technology but one that uses various technologies to come up with a working model. The best course in AI will be covering multiple fields and having the expertise of the leaders of the industry.

This Imarticus course Certification In Artificial Intelligence & Machine Learning is conducted by IIT Guwahati. It not only covers a wider and relevant field in AI and ML but also conducts various discussions, exercises, projects, and assessments with the help of experts and mentors. This is one course that will help you be updated with the latest technologies. The Capstone project will help boost your knowledge and experience in the required field. 

Conclusion

Having someone with an Artificial Intelligence certification can help a company assess the various aspects of digital marketing and fine-tune the process by eliminating unnecessary segments and diverting attention to the most useful ideas and their implementation. Influencer marketing is one such advantageous segment of digital marketing that helps improve engagement rate and content quality. It has helped the leading brands in achieving their goals quickly and accurately. 

Supply chain analytics course: Reimagine organizational operations by fusing design thinking with cutting-edge technologies

Posted on by Imarticus Learning

Supply chain analytics is vital for corporate success because it directly influences a company’s capacity to provide a pleasant customer experience while accounting for many expenses that impact overall profitability. The supply chain is a network that connects suppliers, businesses, and end-users, and it includes everything from acquiring raw materials to delivering products to customers.

Companies can collect, analyze, and act on data created by their supply chains using supply chain analytics. It enables them to make immediate adjustments and long-term strategic improvements to provide a competitive edge.

Hence, what is the need to become a supply chain analyst? Supply chain analytics is becoming increasingly important in the day-to-day operations of today’s most successful firms. Organizations are paying more attention to these figures than ever before, and they’re utilizing a variety of analytics approaches to improve each connection in the network. We at Imarticus help you learn about the supply chain with our SCM program.

best supply chain management coursesTypes of Supply Chain Analyst

Mainly there are four types of supply chain analytics, and we at Imarticus, through the SCM program, brief about them:

Descriptive Analytics

Descriptive analytics examines the past and recognizes trends in historical data. This data could come from internal and external systems that provide visibility across suppliers, distributors, sales channels, and customers. Analytics can uncover patterns and postulate potential reasons for change by comparing the same type of data from different times.

Predictive Analytics

Predictive analytics assists businesses in predicting what might happen and the business impact of various situations, such as supply chain interruptions and other outcomes. Leaders can be proactive rather than reactive by forcing them to evaluate these prospective circumstances before they arise. They have enough time to plan a strategy for a potential surge or drop in demand, for example, and can react appropriately.

Prescriptive Analytics

Prescriptive analytics combines descriptive and predictive analytics data to propose what actions a company should take right now to achieve its objectives. This type of analytics could aid businesses in resolving issues and avoiding significant supply chain interruptions by assessing internal and external data. Because prescriptive analytics is more complicated, powerful software can quickly handle and analyze large amounts of data.

Cognitive Analytics

Cognitive analytics aspires to mimic human thinking and behaviour, and they can assist businesses in answering challenging, complex problems. Though, when it comes to evaluating data, these analytics can recognize things like context. Cognitive analytics utilizes artificial intelligence (AI), notably machine learning and deep learning to accomplish this.

It also allows it to learn and improve over time, and it may drastically cut the time taken by employees to develop these reports and analyses. It also empowers employees outside the data science team to access and comprehend the data.

Benefits of Supply Chain Course

The supply chain analytics report and dashboards assist businesses in identifying and understanding potential risks, improving planning inventory management, and better meeting the high expectations of their consumers. It can help with planning by providing more precise estimates, allowing you to put all of the operational components in place to match the anticipated volume.

The supply chain analytics course training at Imarticus SCM program, we help you to develop the metrics and numbers to help businesses meet customer expectations.

Machine learning with python: How to get started?

Posted on by Imarticus Learning

Machine learning is a process whereby the program will automatically detect a meaningful pattern in the provided data. It is a computer program that comprehends data independently without a programmer. With the passage of time and advancement in technology, the potential to interpret information has improved. Now, machine learning programs can predict more accurate results.

Machine Learning with Python

The machine learning program processes a large volume of data. Therefore, to create this program, a programmer should know Python. But what is the need for analytics to learn Python? Python is the object-oriented program language that uses fewer lines of code. Because of its easy syntax, we can also call it a ‘beginner’s language’.

Python is easily accessible to beginners because of its simplicity and versatility. Coders and analytics can accomplish tasks more quickly with fewer lines of code.

Python Library for Machine Learning   

 At Imarticus, we consider Python the ideal language for learning new concepts. So, the first and foremost step for analytics is to learn Python. The next step is to decide the library you want to use for machine language.

Following is the list of some of the libraries that we, at Imarticus, include in Data analytics and machine learning certification:

1.NumPy

NumPy or Numerical Python is one of the influential Python libraries. It provides a fundamental data structure, and it also has NdArray objects that allow users to create N dimension arrays. These objects are several times more efficient than the in-built Python data structures.

The reason to use NumPy as the foundation for other libraries is that its data structures somewhat cover Python’s speed weakness.

2.SciPy

SciPy is among many other libraries that are on NumPy. It is a very effective tool for sophisticated scientific computation. It introduces advanced algorithms for data handling and visualization by using N-dimensional arrays.

SciPy handles the most complex data manipulation as it is well-documented, supported, and intuitive.

  1. Matplotlib

Matplotloib specializes in data visualization. A well-designed visualization is a crucial component of any machine learning company. After all, training your machine learning algorithms to identify patterns is pointless if you can not interpret the findings.

Generally, every popular Python IDE supports Matplotlib. However, such adaptability comes at the expense of usability; it is not as user-friendly as rival data visualization frameworks.

  1. Theano

Theano creates multi-dimensional arrays and makes advanced mathematical operations possible. It is an excellent tool for machine learning which has its integration with NumPy. In many ways, it is an advanced form of NumPy that makes Python as efficient as C or R.

5.TensorFlow

TensorFlow is a Python-based open-source machine learning library. As Google developed it, almost every Google application that utilizes machine learning uses it. For Google photos or even for Google voice search, we use TensorFlow.

TensorFlow has a fast speed, and it has extensive documentation and support. As it is a Python front-end written in C or C++ is a little difficult to understand.

 

  1. Keras

Keras is a high-level library for datasets. It is widely renowned for being one of the most user-friendly machine learning libraries available because it is written in Python and uses either Theano or TensorFlow as a back-end.

It is the most user-friendly machine learning library, with features for building training datasets and more.

The neural networks API of Keras was designed for rapid experimentation and is an excellent choice for any deep learning project requiring rapid prototyping.

In the driver’s seat: Driving value realization in supply chain analytics courses

Posted on by Imarticus Learning

The supply chain system is a build-up of many aspects put together — from demand to manufacturing to transportation and many more. These aspects together are called the drivers in the supply chain system. As such, their value in the system is irreplaceable. This is why learning about them or realizing their value is essential if you are thinking about a career in SCM.

For that, what is primary is for you to pursue a course on supply chain analytics that will help you cover all the basics. Thankfully, a lot of institutions in India offer a compact supply chain analytics course that will help you get ahead in your career. 

Imarticus Learning, with its years of experience and placement offers, ranks in one of the topmost positions. Their supply chain management course with analytics will not only help you become a supply chain analyst with highly sought-after skills but their placement offers will help you to land a job in your dream sector right from the get-go. Here, we are going to talk about the value realization of the drivers in the supply chain management system and how supply chain analytics courses should focus on them in detail. Please read the whole article to learn more.

Production

One of the major aspects or drivers of the supply chain management process is, of course, production. That includes, what is produced, how much is produced, and also the whole manufacturing process through which it is produced. As such, in the supply chain analytics course, realizing the value of this driver is imperative. 

Inventory

Source materials, products still in the manufacturing process, as well as finished products are referred to as inventory in the supply chain management system. Their value lies in determining the storage places as it directly impacts the responsiveness of the supply chain as well as the retailer’s efficiency. As any change in the inventory greatly affects the supply chain system, their value realization in the supply chain analytics course puts the students way ahead in their careers.

Shipment

Shipment or transportation is yet another core driver of the supply chain management system. The inventory is moved from one place to another through transportation means. As such, its importance is quite irreplaceable in the system. The modes of transportation greatly affect the efficiency as well as the responsiveness of the system. Learning about how to manage a smoother and more efficient mode of transportation in the supply chain analytics course will help the students immensely in their careers later.

Factory Location

Facilities or factories are the places where inventory is stored to assemble them into finished products. As such, deciding their location, capacity, as well as adjustability of the facilities, will impact the supply chain management system massively. Learning to make such decisions quickly and as accurately as possible is one of the most sought-after qualities in a supply chain analyst. Their value realization in the analytics course is a huge way to move forward in your career.

Information

Information, by far, is possibly one of the most important drivers in the supply chain management system. It consists of data regarding inventory, facilities as well as transportation, and clients throughout all the points in the supply chain. As it affects all the other drivers in the supply chain it is absolutely necessary for making the system highly efficient and responsive. As such, learning how to read, store, and analyze said data is one of the skills that make an efficient supply chain analyst. 

Conclusion

Driving value realization is an important part of the supply chain analytics course as it directly impacts how the students will perform in their careers later on. Thankfully, with Imarticus Learning’s IIT supply chain management and analysis course, you can now have all these basics covered and get the boost you need in your career.

7 simple hacks to speed up your data analysis in Python

Posted on by Imarticus Learning

Python is a high-level programming language with a built-in data structure with dynamic typing and data binding. It is general-purpose and straightforward to use the language used to create various computer programs. At Imarticus, we help you learn Python online through the PGA program.

Python creates various programs like developing websites, task automation, software, data analysis, and data visualization. Python is an easy-to-learn language; it is shared between accountants and scientists. It is also used to organize finance and numerous other day-to-day chores.

Python and data science go hand in hand with each other. The data analysts use this language to conduct complex statistical calculations, create data visualization, manipulate and analyze data. Python in web development is pervasive; it includes sending and receiving data processing data while communicating with the database. It also helps in the routing of URLs and ensuring security. 

Python is a dynamic language supporting structured and object-oriented programming. It is the language that focuses on readability, and it is the most accessible language that is why it attracts developers and thereby has a large developer community. 

Python helps in data analysis through the following steps:

  • Python helps to efficiently perform high computational tasks with libraries like Pandas and Numpy.
  • Libraries like beautiful soup and scraps help extract data from the net.
  • Python libraries like Matplotlib and Seaborn help in the analysis of pictographic representation and visualization of data.
  • The Scikit-learn library in Python makes complex mathematical calculations efficient and straightforward.
  • Python library such as OpenCV handles the operations on the image. 

Data Analysis With Tableau

With the PGA course at Imarticus, we help you learn Tableau, data visualization, and data analytics. This course will help you build interactive dashboards and publish them on online Tableau. 

Data analytics is the presentation of data with a blend of colors, dimensions, and labels to create a visualization for providing insight into business and making informed decisions. It is an unavoidable aspect of business analytics as it helps enterprises analyze trends and make decisions quickly and visually. For this visualization and data discovery, you need the Tableau tool.

For business intelligence and data visualization, you need Tableau as it is easy to learn, fast to use, and intuitive for consumer use. 

Data Analysis Using SQL

SQL is the database querying language that helps simultaneously interact with multiple people’s databases. One of the most flexible languages combines a learning curve with a complex depth to help users create tools and dashboards for data analytics.

SQL is famous for quick creation and interaction with the database, and it is also a simple language performing complex data analysis. This language uses many valuable tools such as excel popular python libraries like pandas combined with its internal logic to interact with the data sets. 

So, what are the ways to use SQL for data analytics? SQL uses its base infrastructure and easy-to-use dashboards and reporting tools for communication with complex instructions and fast manipulation of data. One of the other interesting properties of SQL is simple accessibility, strategic organization, and simple, manageable, and understandable interaction. 

Through the PGA program at Imarticus, we help you unfold many uses of SQL in data analytics, such as direct integration into other frameworks, additional functionality, and the ability to communicate effectively. SQL is the tool that acts as an intermediary between the usage and storage of complex data and the end-users, and for using this tool, you need to know Python.

Does Machine Learning Excite You? Check Out Our Data Analytics Course!

Posted on by Imarticus Learning

Machine learning (ML) is truly a blessing to modern computing and technology, possessing the ability to endow systems and machines, the ability to think for themselves and tackle tasks on their own without any supervision of humans. Machine learning is able to do this by creating artificial neural networks which simulate how human brains work. Machine learning is assisted by data science and supports its applications in various fields.

Even though machine learning was initially invested upon with the primary focus on Artificial Intelligence, it was later recognized as a separate field and started being heavily invested upon from the 1990s and is one of the most valuable fields of computing that has one of the highest industry requirements of skilled professionals and freshers holding expertise in various skills and tools which assist in machine learning.

In this article, we will learn more about machine learning and how a well-planned data analytics course can help you progress in your career if you are already in this field or how it can help freshers get exposed to ML. 

What is machine learning?

Machine learning first came into existence due to the interest of having systems and computers learn from data on their own. “Machine learning” was first termed by Arthur Samuel in 1959, who was working in IBM at that time. During his tenure there, he was responsible for various important projects related to computer gaming and AI. It all started when Mr. Samuel took the initiative to teach computers how to play games through the game of Checkers on IBM’s first commercially available computer, the IBM 701.

Eventually, machine learning started being used for various purposes and borrowed many models and approaches from statistics and probability theory. AI uses predictive analytics along with machine learning to execute the various responses or trigger actions. All of this is acquired from the training data set which helps the machine in learning and equips it with the information.

Machine learning is an important branch of computing and data science that creates autonomous systems which learn from data on their own. A machine trained with clean processed data eventually identifies trends and patterns to respond to situations without human supervision.

Machine learning also promotes the automatic improvement and development of algorithms or data models which improve on their own. Machine learning is an important part of Artificial Intelligence which uses data mining, predictive analytics, and various tools to assist machines in learning more extensively with methods like deep learning to allow them to execute functions that emulate the responses of a human, just much more accurate and fast.

Machine learning is also not biased unless specifically asked to do so, hence promoting unbiased AI-supported systems that make fewer errors. Data mining is also a very relevant field and quite valuable to machine learning as it helps systems come to conclusions without having some bits of data or having unknown bits of information. Machine learning is a type of predictive analytics which is backed by data and is exploratory in nature.

Perks of a Data Science Prodegree from Imarticus

The Data Science Prodegree is a great data science course that students and working professionals can choose to gain more exposure and skills in the fields of machine learning, business analytics, and AI.

 

  • Acquire skills and learn how to use required tools and algorithms
  • Gain valuable industry and course certifications
  • Get placement support and opportunities from the best companies
  • Advanced live classroom learning supported by technology and real-life projects

 

Imarticus’s Data Science course with Placement is a great choice if you wish to advance in your career and learn about machine learning, AI, business analytics, or data analysis which will help you become more effective as a data scientist and pursue your dream career in this respectable field.