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The big 5 predictions for Machine Learning certifications in 2022

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The big 5 predictions for Machine Learning certifications in 2022

The future is AI. Machine learning is no longer just an aspect of artificial intelligence but one of the most pivotal building foundations of innovation and new possibilities. 

So, what are the top 5 predictions for Machine Learning and AI:

AI solutions will infiltrate the corporate world – In the past few years, the demand for data scientists has skyrocketed. With digitization taking over, manual labor had to be replaced with the likes of AI. Last year witnessed a boom in the application of AI to compensate for the turmoil in the labor supply chain. Customer service solutions turned to AI with chatbots and various other automated services to combat the pandemic’s impact on labor and businesses.

With technology advancing alarmingly, businesses have no choice but to adapt to AI. AI has become the oil that keeps the corporate world running smoothly today and businesses that don’t adopt new technology are not far from falling out of the race. 

More and more students will enroll in machine learning courses – Machine learning has become an indispensable need in the corporate world. With businesses looking to expand, data has become an integral part that demands data scientists who can decode it and analyze it to provide innovative solutions to real-time problems. Machine learning examines complex data automatically and companies need data scientists who can give them insight into bigger data by creating an algorithm that they otherwise wouldn’t have access to.

With the increase in demand for data scientists, more and more students will turn to courses like machine learning with python or learn data analytics online via the various courses available on the internet. Increased creative AI – Today, whenever we go on the internet, we see online mascots and other characters that aren’t real people. They’ve been created through the application of AI. Several different industries like music, fashion, and art have been using AI for years now to generate creative content.

Although AI has not yet penetrated mainstream media, given how fast technology is gaining ground, a computerized version of today’s mainstream content like AI-generated award shows is a powerful possibility. 

Synthetic data generation

2021 witnessed companies struggling to acquire data and manage it efficiently. It is but natural that they would turn to technology that would enable them to generate synthetic data. 

What is synthetic data? Synthetic data is not based on data collected from the real world instead, it is data that is created via an algorithm. Synthetic data comes with its own set of security and privacy features which can prove to be extremely beneficial to companies. It has been predicted that by 2025, synthetic data will be accountable for 10% of data generated in its entirety.

The healthcare unit and marketing domain are gradually but most definitely switching to synthetic data. Renowned companies like Apollo are fabricating synthetic datasets to be used in line with autonomous vehicles. As more professions start experimenting and incorporating synthetic datasets to create unique products and services, we will eventually see the rise of this form of data in every aspect. 

AI and machine learning will be key to achieving sustainability – Industries today are trying to adopt more sustainable forms of technology. From small startups to major brands in the fashion industry, attaining sustainability has become the prime theme for most companies and the adoption of AI has played an important role in working towards achieving that goal. 

Conclusion

AI and machine learning have become imperative in the innovation and development of society. The need to consistently model tune AI is critical to creating an ethical and efficient future for machine learning. 

Can an Artificial Intelligence and Machine Learning Certification Push Your Career Forward?

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Can an Artificial Intelligence and Machine Learning Certification Push Your Career Forward?

Introduction

Countless professionals, office workers, job seekers, and aspirants are aware of the employment opportunities in artificial intelligence and machine learning and are prepared to provide their services to employers. AI and ML are considered valuable for entrepreneurs planning to increase their business and differentiate the services they provide.

The number of professionals with AI and ML certifications is growing in response to the increasing demand for these technologies in businesses and organizations. If you want to keep yourself updated and are interested in working in Artificial Intelligence and Machine Learning, you should consider a certification course in artificial intelligence and machine learning. 

Alternatively, if you have a Bachelor’s or Master’s in Computer Science, Engineering, Maths, Statistics, or Science with a minimum of 50% marks and do not know what to do next, you should consider this certification. An artificial intelligence and machine learning certification can give you the edge to get the promotion or job you’ve been coveting.

What is the value of an AI and MI certification?

Artificial Intelligence and Machine Learning are great career options–many industries have now consented to using AI and ML. These technologies have applications in several sectors–IT, aerospace, healthcare, robotics, banking, and finance. The Economic Times has predicted that there will be about 3 million jobs in this sector. 

If a person is skilled and equipped with an in-depth knowledge of AI and Ml, they will find it easy to grab a good job with a handsome salary in a multinational firm or any industry mentioned above. Job seekers can also find jobs on platforms such as NAUKRI.COM, which have approximately 15000 jobs for people interested in the field.

In India, the average wage of a professional Artificial Intelligence worker is about Rs. 15,70,800. Apart from the base salary, skilled individuals can use AI and ML certification to enhance their package and position in a company. 

Features of Artificial Intelligence and Machine Learning courses

  1. The courses will teach you extensively about AI and ML technologies and their application. We’ll cover topics like Deep Learning, Computer Vision, Natural Language Processing, Reinforcement Learning, Neural Networks, and TensorFlow.
  2. The course provides learners with practical, hands-on learning in AI and ML labs and 12+ projects.
  3. Students get to work alongside world-renowned companies such as Uber, Netflix, Google, and Amazon.

Benefits of Artificial Intelligence and Machine Learning certification

  • Growth in demand

The demand for AI and related technologies will exponentially increase in the next few years. Businesses will switch to AI to generate better solutions and implement customized internal solutions. 

  • Almost every sector uses AI

If you master AI, you will have many career opportunities available in multiple industries. Many people want to be good at specific branches of AI, such as Deep Learning and Natural Language Processing. Being adept at these offers a chance at a great career.

  • High salary 

The median salary for an AI engineer in the USA is USD 130,000. As the sector keeps growing, domestic industries too will start moving towards fairer pay scales.

  • Better chances of getting a job interview 

Obtaining an AI certification can ensure that you get an interview callback. The AI certification will stand apart on your resume and help you get noticed in the pool of applicants.

Problems you can face while getting an AI and ML certification

Mastering AI and ML technologies can be difficult. Collecting data is a big problem faced by students in their careers. For problem-solving and analytics, one will have to request data from clients. The quality of the data obtained will determine how accurate the output will be. 

A career in AI and ML

To pursue a career in AI and ML, one should be mindful of the following facts:

  • You must understand different technologies in Artificial Intelligence and Machine Learning.
  • Focus on the basics of AI and ML.
  • Knowing about the methods that organisations use on their platforms can be an added advantage for job seekers.

Conclusion

A certification course in Artificial Intelligence and Machine Learning from Imarticus Learning Private limited will help you achieve your learning objectives. You can contact Imarticus Learning Pvt. Ltd through chat support, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Companies that hire employees with AI-certified skills will be setting themselves up for success as those skill sets continue to grow in demand. Certification isn’t just an opportunity; it’s an investment in your future and a safeguard against economic uncertainty.

5 Qualities The Best People In The Artificial Intelligence Industry Tend To Have

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5 Qualities The Best People In The Artificial Intelligence Industry Tend To Have

Working in the artificial intelligence industry is no easy task. This sector is growing at a fantastic rate, and this growth shows no sign of slowing down. Every day new companies are popping up, and more general businesses are looking to get involved with machine learning programs. This means there is a high demand for developers with skills in artificial intelligence. 

Artificial intelligence (AI) technologies have grown in recent years. Our daily lives get impacted by these artificial intelligence applications, which range from self-driving automobiles to robots serving meals in restaurants. AI primarily creates intelligent systems and software based on how human minds reason, learn, make decisions, and solve problems. It lets robots know via experience and carry out tasks similar to humans. But what exactly makes a good AI candidate? 

Here are five qualities that the best people in the artificial intelligence industry tend to have:

Love of learning: AI requires constant learning and development. You’ll need to be able to learn new skills quickly so that you can adapt as technology changes over time. 

Creative thinking: Creative thinking is essential if you want to create something original with AI—an algorithm that detects faces in images or an app that automatically generates high-quality music based on your taste preferences.

Emotional intelligence: Being able to deal with emotions daily will help you better understand how humans react when faced with difficult situations—and thus better handle those situations yourself when they arise in your life! 

Be able to explain complex ideas: They’re able to explain difficult concepts easily. They can do this through strong writing skills or by communicating with clarity and precision.

Strong work ethic: These professionals are willing to put in the time and effort necessary to achieve their goals—and they don’t give up easily when things get complicated.

These qualities are essential for people who want to work in AI because it takes a lot of dedication and discipline to learn how it works and then figure out how you can use it for your purposes. AI is essential since it is the fundamental building block of computer learning. 

Learn AI and Machine Learning Courses with Imarticus Learning.

Corporate leadership

Attend the E & ICT Academy deep learning Artificial Intelligence certificate program to discover how to become an AI engineer. This IIT AI ML Course will help students prepare for careers as data scientists, data analysts, machine learning engineers, and AI engineers. 

Course Benefits For Learners:

  • To get practical industrial experience and prepare for a fulfilling data science career, students work on 25 real-world projects. 
  • You may amaze employers and demonstrate your talents with a certificate authorized by the E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed credential. 
  • This artificial intelligence course will help students land lucrative jobs in machine learning and artificial intelligence.

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

Machine Learning: An overview, trends and careers

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Machine Learning: An overview, trends and careers

If you’re looking for an exciting, challenging, secure, and successful future, then you can consider choosing a machine learning career. And if you don’t already know, it was recently declared one of the most sought-after AI jobs, with rapid digitalization and a greater focus on advanced fields like machine learning and artificial intelligence. 

In the past four years, machine learning and AI jobs have increased by a whopping 75% and are continuously growing. This indicates that working in a machine learning job can help you secure your future and earn your dream salary by serving an industry that is increasing in demand. In this article, we will discuss what machine learning is, and how you can build a successful career in this field. Read on! 

What is Machine Learning?

In simplest terms, machine learning is a field of AI. It helps in building self-learning automatic systems that can enhance their performance with their experience and without any human intervention. This allows machines to make data-centric decisions. Whatever a machine learns from its experience and available data, it can be used for making predictions. For instance, if you have used Google maps, then you might have noticed that sometimes it shows the fastest route with less congestion and traffic. It is able to do so with the help of machine learning algorithms. 

Machine learning engineers build these algorithms in such a way that they get used to experiencing and exploring fresh data for making predictions. This quality of machine learning provides businesses and organizations with the ability to make better strategies and optimize their operations to grow and succeed in their respective industry. 

What Does a Machine Learning Career Path Look Like? 

A career in machine learning usually begins with a post of machine learning engineer. A machine learning engineer builds solutions and applications that automate tasks that are previously handled manually. Most of these are repetitive tasks that are based on specific action pairs and conditions — which a machine can perform efficiently without any error. 

Once you earn a promotion as a Machine Learning engineer, you become a machine learning architect. Individuals in this job are responsible for creating applications and prototypes that need development. Some other job roles available in the field are ML software engineer, ML data scientist, ML senior architect, and so on. 

What Skills Do You Need for Machine Learning? 

Given below are some ML areas as well as skills required by the professionals:

Statistics and Probability 

A majority of machine learning algorithms have their base in mathematical concepts like Markov models, Bayes theorem, and a few other areas of probability. Furthermore, concepts like mean, deviation, median, and Poisson distribution are also very important in ML. 

System Design

Machine learning solutions are not generally standalone in nature. Instead, they are an important part of an integrated technical economy. This is the reason machine learning professionals have a good knowledge and understanding of software design. 

ML Algorithms and Libraries

ML professionals swear by models like Bagging, Linear Regression, Boosting, and Genetic Algorithms. 

Data Modeling

As a machine learning enthusiast, you should be able to evaluate the structure of datasets in order to identify patterns, correlations, and clusters. Further, data modeling is also necessary to make sure that data models are on point. Moreover, ML practitioners should also know how to test data for its accuracy and integrity. 

Programming Languages

Finally, if you want to pursue a machine learning career then you should have great proficiency in programming languages. Note that Python is the most important programming language for machine learning. Besides, technologies like Apache Spark, SAS, and AWS, are also crucial in ML. 

Know that this isn’t the list of only skills you need to acquire to have a career in machine learning. There are several other concepts and modules that you should learn to become an ML professional. The best way to begin your career in this field is to learn machine learning by enrolling in the right machine learning course. Further, you can also consider taking a machine learning certification program from a reputed institute. 

Scope and Salary Trends of Machine Learning 

As compared to other career options, the scope and demand for Machine Learning are very high in India as well as abroad. According to a Gartner survey, there will be more than 2.3 million jobs in the field of AI and ML by the end of 2022. 

Moreover, ML jobs offer a much higher salary than other jobs. As per the Forbes report, the average salary of an entry-level ML professional is $99,007 in the US. This converts to INR 865,257 in India. 

As you can see, machine learning is a booming career field that can help you build a successful and secure future. So, don’t wait anymore and start your career in this lucrative field by taking the right machine learning course! 

Data science and machine learning professionals are career optimistic – The statistics show why.

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Data science and machine learning professionals are career optimistic – The statistics show why.

Advanced technologies like artificial intelligence and machine learning have grown rapidly in recent years. They are expected to grow further in the upcoming years at the same lightning speed.

As per a forecast, the artificial intelligence market is expected to grow at a Compounded Annual Growth Rate (CAGR) of thirty-eight percent from 2022 to 2030. The adoption of artificial intelligence and machine learning can be seen across various sectors like healthcare, finance, automobile, and finance, to mention a few.

This will give rise to the demand for data science and machine learning professionals in various job roles across these sectors. Individuals having the skills and expertise in artificial intelligence and machine learning will be recruited from the junior-most to the senior-most levels on a large scale.

Job Roles Available for Data Science and Machine Learning Professionals

As stated earlier, there is a myriad of job roles available for data science and machine learning professionals in various industries. Some of the job roles include:

  • Machine Learning Engineer
  • Business Intelligence Developer
  • Software Developer
  • Natural Language Processing (NLP) scientist
  • Computational Linguist
  • Data Scientist
  • Data Engineer
  • Marketing Analyst
  • Business IT Analyst
  • Data Architect

Why Data Science and Machine Learning Professionals Are Optimistic

We are living in a world of big data. The amount of data produced is increasing with each passing day. It is estimated that the volume of global data will reach 180 zettabytes by 2025. There will be a huge demand for professionals who can handle, manage, and convert this huge volume of data to derive actionable insights that can help businesses enhance and expand their operations.

As per a report, there were over one lakh job opportunities in the data science domain in India in June 2021. Data science jobs witnessed a forty-seven percent increase in requirements in 2021 compared to 2020. This is despite the COVID-19 scenario.

Another report has monitored the continuous rise of artificial intelligence and machine learning. It found out that data science jobs have witnessed a tremendous six hundred and fifty percent growth since 2012. The rise is set to continue in future years. It is estimated that the growth of data science will create more than eleven million job openings in the field by 2026.

These trends, therefore, indicate that now is an opportune time to start a career in data science. Thus, you will be required to acquire the requisite knowledge, expertise, and skills in artificial intelligence and machine learning domains.

Benefits of Choosing a Career in Data Science and Machine Learning

So, why choose data science as a career option? Let’s look at some of the major benefits of being a data science and machine learning professional.

  • Ever-Increasing Demand

As stated earlier, the demand for data science, artificial intelligence, and machine learning professionals is only expected to increase further in the future. Thus, there will be no shortage of jobs in this field.

  • High Salaries

Data science and machine learning professionals earn handsomely, irrespective of their job position, experience, and organisation. Some of the average annual salaries in different job roles are discussed below.

Thus, we can see that data science and machine learning professionals are some of the best-paid individuals. In addition to such fat packages, they are also entitled to bonuses, incentives, paid vacations, stock options, and other perks, depending upon the organisation.

  • Versatile Field

Professionals can find job opportunities in various sectors like manufacturing, retail, eCommerce, and healthcare. They can also switch easily from one field to another if they want to explore other domains. Thus, unlike most other career paths, data science and machine learning professionals aren’t tied to one particular field.

Skills Required for Data Science and Machine Learning Professionals

To be successful, professionals need to possess certain skills that can help them excel in their work and enable them to climb the professional ladder quickly. Some of the skills include:

  • Problem-solving intuition
  • Analytical and critical thinking
  • Business sense
  • Communication
  • Mathematics and statistics
  • Programming
  • Management
  • Leadership
  • Cloud computing
  • Data visualisation
  • Calculus
  • Data wrangling
  • Machine learning
  • Deep learning
  •  DevOps
  • Business Intelligence tools

To acquire these skills, you will need to complete a certification course in artificial intelligence and machine learning. You can opt for such courses after completing your bachelor’s or master’s certification.

While there are tons of courses out there, we recommend you check out Certification in Artificial Intelligence and Machine Learning offered by E&ICT academy, IIT Guwahati. Some of the program highlights include:

  • Industry-approved curriculum
  • Real industry projects
  • Certification by IIT Guwahati
  • Live online training

The 9-month course will impart the foundational skills that can prepare you for diverse roles in the data science and machine learning domain. Individuals have landed lucrative job roles in top companies like Accenture, Wipro, HSBC, and Oracle, to name a few.

Want to learn Machine Learning IIT AI Course? Feel free to contact our chat support. Alternatively, you can also visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. We would be more than happy to serve you.

Explore Machine Learning: Here’s How to Find Your Way Through the Data Science Maze

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Explore Machine Learning: Here’s How to Find Your Way Through the Data Science Maze

The term ‘Machine Learning’ was coined in 1959 by then-IBM computer scientist Arthur Samuel while designing a computer algorithm for the classic game of Checkers. Today, this term is immensely popular owing to the technology’s wide application across industries.

But what is Machine Learning or ML? It is a computational method that is used to obtain artificial intelligence by making a machine learn how to solve problems on its own rather than requiring explicit programming software. 

Machine Learning is widely used in the field of data science as it helps find the way through tons of data instantly and accurately! But how? By using statistical methods and algorithms to train computers so that they can accurately classify data sets and make reliable predictions to uncover key data insights.

Does all this sound interesting to you? Do you aspire to use advanced Machine Learning technologies to solve real-life problems and arrive at data-driven solutions? If yes, then you should check out our data science courses which are equipped with not only data mining techniques but also machine learning tools along with Python, SQL, and Tableau.

Machine Learning Concepts Which Every Data Scientist Must Know About

Data science learners must be able to develop a solid foundation and specialise in machine learning with Python for data-driven decision-making. Ultimately, you want to assist organisations to make smart decisions for growth and offer insightful data analysis.

Following are some of the key Machine Learning tools which you must know about if you are aspiring for a data science career:

  • Clustering

CLustering is the simplest unsupervised ML method that lets the algorithm define the output for mining data. The most famous clustering method is ‘K-Means’ under which the letter ‘K’ refers to the number of clusters into which the miner wants to divide the unlabelled data. 

The clustering method is used for drawing analysis in varied fields such as for creating customer segments for different marketing techniques as well as for identifying earthquake-prone areas.

  • Neural Networks

If you are interested in the Deep Learning subset of ML, then you must know Neural Networks in and out. Neural Network is a network of algorithms that identify patterns or relationships among different data points in a set in a way similar to the working of a human brain. 

It is widely used for making forecasts and improving decision-making in fields like stock market trading, medical diagnosis, etc. You can learn more about neural networks in our data science online training programs.

  • Regression

Regression is one of the fundamental supervised ML techniques which help data scientists in creating predictive models by defining a relationship between dependent and independent variables. 

There are various types of regression models, however, broadly they can be classified into three groups: Simple Linear Regression Model (SLRM), Multiple Linear Regression Model (MLRM), and Logistic Regression.

  • Natural Language Processing (NLP)

Natural Language Processing (NLP) forms the basis of Machine Learning as it trains machines to learn the language of humans. You can find some of the everyday applications of NLP in voice-controlled applications like Apple’s Siri, Google Assistant, Amazon’s Alexa, etc. NLP is also found in execution in the fields of text summarization and sentiment analysis. 

  • Ensemble Methods

The concept of the Ensemble Method is quite similar to that of assembling. For instance, if you are not happy with all the car options available in the market and wish to come up with a car design, you can assemble your favorite car parts of different cars and design a car of your choice. 

Similarly, if as a data scientist, you are not convinced with the results of different predictive models, you can combine all of them to arrive at better predictions.

  • Transfer Learning

Transfer Learning is one of the efficient ML techniques which lets you use parts of previously programmed neural nets to develop a similar model. For instance, if you are a data scientist who has developed a technique to filter different styles of men’s clothing in buckets like shirts, t-shirts, kurtas, etc., you can use parts of transfer learning to develop a mechanism that can be used for categorising women’s clothing in say, dresses, jumpsuits, tops, etc.

Takeaway

Machine Learning has become a crucial part of the data science field today, which has made the process of analysing and predicting data faster and more accurate than before. 

Be it for real-time navigation, or product recommendations, as a data scientist you will always find Machine Learning and Data Science going hand-in-hand. And the future of data science is expected to be even more promising with the advancements in ML techniques and methods.

Thinking of kickstarting your data science career? Contact us through chat support, or just visit our nearest training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon.

Our Certificate Program In Data Science And Machine Learning is created by iHUB DivyaSampark at IIT Roorkee and will instruct you on the fundamentals and features of data science and machine learning and give you the skills necessary to put these ideas into practice and apply them to real-world issues.

IIT Machine Learning: Introduction To The Machine Learning World

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Machine Learning has been a buzzword in recent years, possibly due to the large quantity of data produced by applications, the rise in processing power, and the development of better algorithms.

Machine Learning is employed everywhere, from automating monotonous operations to providing sophisticated insights; companies in every area are attempting to capitalize on it. You could already be using a gadget that makes use of it. 

Introduction to the machine learning world

You may apply machine learning in prediction systems as well. Supervised learning, reinforcement learning, and unsupervised learning are the three categories of machine learning. The computer is given a set of training data together with the intended output and subsequently learns how to produce the desired output using the training data. This process is known as supervised learning. 

When the computer gets a collection of data but not the intended result, it must learn to recognize the structure in the data on its own through unsupervised learning. Reinforcement learning is where the computer gets a set of data and a reward function, and the computer has to learn to produce the desired output to maximize the reward.

Machine learning is a powerful tool that may apply to many tasks, including predictions, voice recognition, and face and facial expression detection. 

Application of Machine Learning

 Speech recognition is the procedure of converting spoken words into text. Speech dialing, call routing, and appliance control are all examples of voice user interfaces. You may also use it for simple data entering and structuring papers.

One of the popular uses of machine learning is image recognition. It recognizes items, people, places, digital photos, etc. Facebook has an auto friend tagging recommendation option. When we submit a picture with our Facebook friends, we instantly get a tagging recommendation with their names, powered by machine learning’s face identification and recognition algorithm.

Machine learning techniques are currently widely employed in various voice recognition applications. Google Assistant, Siri, Cortana, and Alexa use speech recognition technologies to respond to spoken commands.

Machine learning is a subtype of AI that allows machines to learn from data, improve performance based on previous experiences, and make predictions. 

Learn Machine Learning and AI courses with Imarticus Learning

Become an AI engineer by attending the E & ICT Academy deep learning Artificial Intelligence certificate course. Students will benefit from this IIT Machine Learning Course as they prepare for jobs as data scientists, data analysts, machine learning engineers, and AI engineers.

Course Benefits For Learners

  • Students work on 25 real-world projects to get industry experience and prepare for a rewarding career in data science.
  • You may impress employers and exhibit your abilities with an E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed credential.
  • This machine learning certification will assist students in obtaining lucrative professions in artificial intelligence and machine learning.

10 Beginner-Friendly Steps To Learn Machine Learning

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10 Beginner-Friendly Steps To Learn Machine Learning

Machine Learning is believed to be the future of data science. According to Forbes insights, the global Machine Learning market is valued at $21.17 billion and is expected to surpass $209.90 billion by 2029. But what is Machine Learning? 

Machine Learning is an advanced technology for making machines learn to work without direct programming or commands from humans. It uses various statistical methods and algorithms that help computers and software identify patterns and produce the desired results.

If you aspire to learn Machine Learning and explore the field of data science, you can start with the steps provided below:

Step 1: Learn Python

The first step toward mastering Machine Learning is learning a programming language to analyse data and derive meaningful insights from it. The most popular programming language in this regard is Python. 

Step 2: Sharpen Your Mathematical Skills

Brush up your mathematical and statistical concepts like probability, regression, calculus, linear algebra, and hypothesis testing. These are necessary as they come in handy for designing and understanding different algorithms and predictive models.

Step 3: Understand How Machine Learning Works

Once you have mastered a programming language and revisited mathematical concepts, you can start picking up different Machine Learning concepts. For starters, you can research the different types of Machine Learning and their applications. Essentially, there are three types of Machine Learning concepts: Unsupervised Learning, Supervised Learning, and Reinforcement Learning.

Step 4: Get Hands-on With Data Science Tools

Start learning different data science tools like the Jupyter Notebook, Anaconda, Apache Hadoop, etc. These tools teach you to create and share documents containing codes, equations, and data visualizations.

Step 5: Learn How To Design and Select Algorithms

An algorithm is a set of rules you use to process a data set. Since a data set contains a large number of data points that are varied in nature, a single algorithm cannot be used to solve it. Thus, you must know how to design diverse algorithms and select the ones that can be used for different data sets. You will acquire this skill only with practice and over time. 

Step 6: Learn Data Visualisation and Manipulation

To implement Machine Learning, you must be able to visualise data with the help of software like Tableau to make sense of it. For this, you must familiarise yourself with software like NumPy, Pandas, and Matplotlib. These tools teach you to visualise and manipulate data and extract meaningful information.

Step 7: Build Your First Machine Learning Model

Once you have mastered all the preliminary tools and software, you should devise your first Machine Learning model. You can use any online platform to create your machine learning model. 

Step 8: Tune Your ML Model

After devising your Machine Learning model, use it to train an algorithm over a data set and see how it works. Based on the results, tune it and add features that can improve its accuracy and speed. 

Step 9: Learn Deep Learning

Move on to acquire Deep Learning skills as Machine Learning works well only with small sets of data; to deal with large sets, you need to know Deep Learning. 

Step 10: Get Practical Experience

As a final step, get some hands-on experience to test your knowledge and skills. You can take up projects or join a Machine Learning internship. Practical experience will help you implement theoretical concepts and boost your confidence by providing actual results.

Take Away

Machine Learning is a rapidly evolving domain. If you aspire to make a career in Data Science and Machine Learning, it will be helpful to start as early as possible. You can either learn the fundamentals through free resources on the internet or take up paid courses to get a better understanding. 

Imarticus Learning offers a certificate program in data science and machine learning, a 5-month weekend course offering comprehensive understanding and live training facilities by the IIT faculty and industry experts. Feel free to contact us through our chat support. You can also visit your nearest training center in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

From zero to research- An introduction to IIT AI/ML course

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AI & Machine Learning in Everyday Life

The importance of Artificial Intelligence (AI) is constantly on the rise and so is its involvement in our everyday lives. Although we don’t often think about it, AI is everywhere.

From chatbots that communicate with us on various online shopping platforms and websites to social media platforms that target audiences and advertise products based on our searches, AI is encoded everywhere. Being such a pertinent part of business, these days makes enrolling in an artificial intelligence and machine learning course a viable option to ensure a lucrative offer in the job market.

Here are 8 ways AI is present in our everyday lives without us even noticing:

  1. Face recognition locking on our phones
  2. Friend suggestions, product/service advertisements based on searches on social media
  3. Spell checkers and Grammarly tools installed on emails and messaging portals
  4. Google searches
  5. Voice assistants such as Siri and Alexa
  6. Smart home devices such as air conditioning machines, electrical switches, refrigerators, and so on
  7. Google maps and other satellite-based trackers
  8. Content suggestions on Netflix based on your watching history

IIT AI/ML Course

Given the way AI is becoming a part and parcel of our lives, the Indian Institute of Technology (IIT) is offering AI/ML specialized courses so that you can gain in-depth knowledge and skills in the applications and techniques associated with machine learning. The idea is to upskill professionals and train them in a manner so that they are ready to take on high-paying jobs in the world’s most demanding computer language.

These are certificate courses that span over a period of 6 months and during this time you will be taught the following subject areas:

  •         Basics of Python
  •         Mathematical Background
  •         Introduction to Machine Learning
  •         Regression Analysis
  •         Optimization in ML
  •         Unsupervised Learning
  •         NLP and text analysis
  •         Feature Selection and Dimensionality Reduction
  •         Reinforcement learning

Outcomes of the Program

  •   Are able to quickly and relevantly gather insights by analyzing data
  • Are able to come up with predictive models that use decision trees and neural networks
  • Can carry out mathematical operations on an array of data
  • Are skilled enough to operate Pandas so that you can manage data, rearrange them and carry out various kinds of analysis
  • Can create text classifications systems making use of learning methods and linear classifiers
  • Professionals can compare optimization techniques and how they effectively solve learning issues across platforms and models to reduce the extent of errors

Who Can Apply for the IIT AI/ML Course?

The artificial intelligence and machine learning course is perfect for anyone keen on learning about machine learning.

Additionally, this program is the right fit for professionals who understand computer programming language and has completed their graduation with preferably a year of practical experience in the industry. You will find this course if you:

  •         Are tasked with machine learning projects or software development
  •         Wish to be at the helm of machine learning projects or want to work in this field
  •         Already have practical knowledge of programming languages such as C, C++, and java

Why Should You Go for this Program?

When you enroll in the artificial intelligence and machine learning course at IIT, you are to get the following benefits:

  • Get a chance to learn and earn a degree from the country’s best engineering school
  • Get a chance to participate in interactive online learning sessions which will be in live mode
  • Will be able to interact and exchange ideas with the best faculty comprising of the top industry professionals
  • Engage in productive peer-to-peer networking and learning
  • Build a strong foundation in concepts such as high-level Python programming, AI, and ML 
  • Participate in the biggest placement on-campus drive

Conclusion:

The importance of artificial intelligence and machine learning courses will continue to be on the rise given the greater involvement of AI in our daily lives. From healthcare, banking, financial institutions, gaming & entertainment to the airline industry, AI is a necessity, and enrolling in the IIT AI/ML course will equip you with industry-specific skills that will help you in every aspect of your professional life.

The two paths from Natural Language Processing to Deep Learning

Posted on by Imarticus Learning

The two paths from Natural Language Processing to Deep Learning

Natural Language Processing is a branch of linguistics, computer science, and artificial intelligence that deals with the interaction between computers and human language, in particular how to design computers to handle and evaluate huge volumes of natural language data. We want a computer that can “understand” the text in documents, including its context and subtleties.

As a result, the papers’ data and insights may be correctly extracted by the technology, which can also classify and arrange the documents themselves.

Massive amounts of unprocessed, text-heavy data need a system like this, which is widely used in machine learning. Professionals with expertise in designing models that analyze voice and language, find contextual correlations, and generate insights from this unprocessed data will be in high demand as AI continues to grow. Natural Language Processing and Deep Learning with Python are one of the most common phrases used in the domain of Artificial Intelligence nowadays.  

In machine learning and artificial intelligence, a technique known as “deep learning” mimics human learning processes. Data science, which encompasses the statistical analysis and forecasting models, relies heavily on deep learning techniques to do its work. For data scientists, deep learning is a godsend since it speeds up the process of processing and understanding massive volumes of data. 

It is possible to think of deep learning as the automation of predictive analytics. Deep learning algorithms are piled in a hierarchical structure of increasing complexity and abstraction, while typical machine learning algorithms are linear.

Neural Networks and Deep Learning

A Neural Network, also known as an Artificial Neural Network, is made up of layers. Imagine the neurons in a human brain; they are the computing units, and they form a single layer when layered. stacking neurons together creates several layers. It is termed the input layer because it contains the data that we are working with. We run our algorithms and get an output, which is then utilized to do our computations for the following layer, the output layer.

At each successive layer, all of one layer’s neurons are linked to those at each successive layer, which are then linked to the next layer, and so on, until we reach our output layer, where we achieve our desired outcome for the specific data we were working with. Those layers that are between the input and output layers are referred to as Hidden Layers. A Neural Network is the result of this process.

A deep neural network is an artificial neural network with two or more hidden layers, and a model built on a deep neural network is referred to as Deep Learning. 

What are the main components of Natural Language Processing?

NLP consists of a number of components, a few of them are mentioned below:

  • Analysis of morphological and lexical patterns.
  • Syntactic Analysis: Study of logical meaning from a given part of the information, be it text or audio.
  • Semantic Analysis: Used to analyze the meaning of words.