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Category: Analytics

Boost your employability with an IIT artificial intelligence and machine learning course

Posted on by Imarticus Learning

The world of work is changing. Many tasks that humans previously performed are now being carried out by machines thanks to the development of artificial intelligence (AI) and machine learning (ML).

This presents both a challenge and an opportunity for workers around the world. Those who can learn the skills needed to work with AI and ML will be in high demand. If you want to boost your employability in today’s economy, consider enrolling in an IIT artificial intelligence and machine learning course!

Artificial Intelligence and Machine Learning

It is an interdisciplinary field that is increasing. Thus, there is a great demand for experts in this field. The promise of real human-to-machine communication is one of the benefits of artificial intelligence (AI). When machines become intelligent, they can comprehend requests, link information, and reach conclusions.

IITs are India’s premier engineering institutes and offer some of the best courses in AI and ML. An IIT course will help you develop the skills needed to become an expert in this field. IITs offer a variety of courses in AI and ML, ranging from introductory courses to advanced research programs. No matter your level of expertise, there is an IIT course that is right for you.

How can an IIT artificial intelligence and machine learning course boost your employability?

 

If you’re looking to boost your employability, an IIT AI and machine learning course could be the perfect solution.

Here will discuss why:

#01. Machine learning is an in-demand skill

Machine learning is the hottest skill in today’s job market. Employers are increasingly looking for candidates with machine learning skills, and the demand for these skills will only continue to grow.

#02. Stay Ahead of the Competition

IITs are at the forefront of machine learning research and development. You’ll get access to the latest and greatest machine learning technology by taking a course at one of these institutes.

This will give you a leg up on the competition and make you more attractive to potential employers.

#03. Get Hands-on Training

When you take an IIT course in machine learning, you’ll get access to some of the best instructors in the world. 

If you’re looking to boost your employability, then an IIT course in machine learning is a great way to do it. With the help of these courses, you can stay ahead of the competition, get hands-on training, and make yourself more attractive to potential employers.

Discover IIT artificial intelligence and machine learning course with Imarticus Learning.

Enroll in the machine learning and artificial intelligence course program at the E & ICT Academy to learn about machine learning online training.

 Course Benefits For Learners:

  • Students work on 25 real-world projects to develop real-world business experience and prepare for a rewarding data science career.
  • With a certificate recognized by the E & ICT Academy, IIT Guwahati, and a credential supported by Imarticus Learning, students can attract employers’ attention and demonstrate their skills.
  • Students who complete this IIT AI course can land lucrative jobs in the machine learning and artificial intelligence sectors.

 Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via the chat support system.

How much time will it take to learn data analysis with Tableau?

Posted on by Imarticus Learning

Data Science and Analysis are among the most highly-demanded branches of computational advancement. It wouldn’t be wrong to say that these fields are driving most of the progress we have seen in recent times. 

If data has been referred to as the new oil, then data science and analysis are the oil rigs pumping oil 24x7x365 and driving the world towards a better tomorrow. However, if you want to learn data science or analysis today, you must also know Tableau. 

But is Tableau easy? How much time will it take to learn data analysis with Tableau? Let’s find out.

What is Tableau, and what is its significance in Data Science and Analysis?

Tableau is one of the inevitable courses in Data science and analysis. Many data science and analysis aspirants wish to learn Tableau but often have misconceptions. They think learning Tableau requires technical training of some sort. So the learning curve might be steep. 

But there is no truth to this. Tableau is not technical at all. Its difficulty level might be equal to that of Excel. You need two to six months at the most to master it.

Basic Tableau is not difficult at all. First of all, let us bust one myth. You don’t require any background in computer programming to master it. Although data analysis might require you to learn a bit of Python, that’s all it is. Tableau does not require you to learn any programming language whatsoever. 

It helps you to represent the data pictorially. Grasping Tableau requires you to understand how its interface works. Once you figure that out, you are good to go. If you have some basic understanding or have used it beforehand, you might also get a head start and complete the course easily. Only three months are required at maximum to master it.

However, starting from scratch, you might need to understand the basics and all the stuff you see on Tableau’s UI. Then you might need six months to learn every bit of the data visualisation tool.

As already mentioned above, Tableau helps us to visualise data. You need to feed in data as a CSV sheet, and you will be able to get a visual output out of it. This way, you can understand what all perspectives can be generated from the data. 

Using these data visualisations, you can make precise solutions driven by the data. There are also some elements of business intelligence along with analytical tools. Tableau has mind-blowing software that can convert raw data into a dashboard you can access. 

Data gets simpler after depicting it visually, and it is then human professionals interpret. They better understand the KPIs (key performance indicators) and provide a better solution to a problem. Those opting for a PG in Data Analytics must choose a course that teaches them Tableau.

The other advantages are that Tableau performs the data analysis extremely quickly, almost in real-time. Visualising data is also stunning, making you easily understand all the data projections and statistics. It eases the understanding process for data analysts and other professionals. Since Tableau doesn’t require any technical background, the data visualisation can be understood by every person in the company, regardless of their professional background.

Other great features of Tableau provide a great advantage to Data analysts as they get more power in their hands. You get options like data blending, which allows you to display data from other sources and perform a comparative analysis. With the help of the data blending feature, you can find out how well you perform against your competitors.

Then there is a collaborative feature of Tableau. You can use a collaboration kit to use the data for reference and comment on it. Since Tableau does not allow and save work in one workbook, you might have to use several collaborators to make the data interactive and more useful for comprehension.

Tableau also allows users to manipulate live data sets. This way, a data analyst can save time on data wrangling and extract much information from the given dataset. The output generated from the raw data is more accessible and understandable. So Tableau is a useful tool for data scientists and analysts.

So, to become a data analyst, you must learn and master Tableau. You must also check whether this is a Data analytics course with placement. Doing a job is the best way to master a skill. But it is going to take some time. That is why you need to enrol in the PG Data Analytics course offered by Imarticus, where everything mentioned above will be taken care of. So, don’t wait; enrol now. 

Frequently Asked Questions

What do you mean by data analytics with tableau?

Tableau is a comprehensive data analytics platform designed for the entire data workflow. Tableau facilitates a seamless process from data preparation and analysis to collaborative efforts and sharing insights. Its strength lies in empowering users with self-service visual analysis capabilities. It enables them to pose new inquiries about well-governed big data and effortlessly disseminate their discoveries throughout the organisation.

What is tableau used for?

Tableau serves as a versatile platform, enabling users to craft a variety of visual elements such as charts, graphs, maps, dashboards, and stories for visualising and analysing data. This functionality is instrumental in aiding business decision-making processes. Renowned for its distinctive and compelling features, Tableau has emerged as a leading tool in business intelligence (BI).

Data analytics is a high paying job?

Indeed, data analysts typically receive competitive compensation. Over the past decade, salaries for data analyst roles have notably increased and remain attractive in today’s job market. As of early 2024, Zippia reports that the average annual salary for a data analyst in the U.S. is approximately $74,000, reflecting the ongoing demand and favourable remuneration for professionals in this field.

Learning Analytics? Discover The Value Of Learning Analytics With A Supply Chain Management Course

Posted on by Imarticus Learning

Supply Chain Management courses are one of the most important aspects of learning about business. They teach you how to manage resources effectively and keep your business running smoothly. 

From 2020 to 2030, the global supply chain market can grow at a CAGR of 10.7%. Accordingly, the market will be worth $52632.37 million by 2030 instead of $18699.45 million in 2020. 

However, did you know that Learning Analytics can help unlock even more benefits from your course? This blog post will discuss the value of Learning Analytics and how it can help improve your Supply Chain Management education!

What is Learning Analytics?

Learning Analytics is a term used to describe collecting, managing, and analyzing data related to student achievement and learning. It helps educators identify student performance patterns over time and adjust accordingly.

 

With Learning Analytics, researchers can unlock a new world of possibilities for understanding teaching and learning. Data infrastructures now allow us to provide learners with instant knowledge through tailored feedback that helps drive better performance – enriching their experience beyond measure. 

At the same time, educators gain invaluable insights that are only possible once persistent data is available regarding instruction methods for individual student progress. 

In short, this innovative field offers powerful advantages no matter where you stand on the educational spectrum!

Why is learning analytics valuable for your supply chain?

The use of learning analytics can be precious for a company’s supply chain. By tracking and analyzing the data associated with how employees learn and use new information, businesses can identify areas where they can improve the flow of knowledge and information within the organization. 

Additionally, analysts can help determine which employees may need additional training to keep up with the latest changes in the field. Learning analytics can help make a company’s supply chain more efficient and effective.

The Value Of Learning Analytics With A Supply Chain Management Course:

  • Improved Knowledge Retention:

Learning analytics can help improve knowledge retention by identifying employees struggling to learn and retain new information. Organizations can develop specialized training programs in this way to guarantee that everyone is aware of new procedures and is on the same page.

  • Improved Performance:

Learning analytics can also help improve employees’ performance and ability to handle new tasks. By tracking students’ progress in a course, analysts can identify which areas need more attention or additional training for tremendous success.

  • Streamline Processes:

You can also use analytics to help streamline processes within the organization by identifying how employees are utilizing new information and applying the knowledge. This can help to improve efficiency by eliminating redundant or unnecessary steps from processes.

  • Improved Decision-Making:

Learning analytics can also provide organizations with valuable insights regarding decision-making. Supply chain managers can better understand how their decisions could affect business operations by uncovering patterns in employee behavior.

By leveraging learning analytics, businesses can unlock a wealth of potential benefits for their Supply Chain Management course.

Learning analytics can be an invaluable tool for businesses looking to improve the effectiveness of their Supply Chain Management course. By leveraging data and insights from learning analytics, supply chain managers can better understand their processes and make more informed decisions about optimizing them. Supply Chain Management courses have the potential to unlock a wealth of value for organizations. 

Explore IIT Roorkee supply chain management course with Imarticus Learning

Professionals looking to maximize their expertise in Supply Chain And Logistics Management should consider certification to equip leaders with the tools they need to drive tactical, operational, and strategic decisions. 

Course Benefits For Learners:

  • Prepare yourself to contribute to creating more tactical and innovative global supply chains by integrating traditional supply chain management course with analytics.
  • Get ahead in the job market and become a Supply Chain Analyst with IIT’s supply chain program. Take advantage of this opportunity to launch your career as an expert Demand Planner or Data Scientist!
  • Python teaches students to be data-centric, which will help them make better supply chain decisions.

Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via the chat support system.

How Data Analyst course can help you enhance your data analysis skills

Posted on by Imarticus Learning

A data analyst is a role within the field of data science that is responsible for collecting, cleaning, organizing, and analyzing large amounts of data. They create reports and visualizations that help businesses make decisions based on the data and help organizations understand how to best use their data to maximize profits and efficiency.

However, a data analyst needs to be adept in data analysis skills, statistical expertise, data visualisation, and Python. A Data Analyst course can help you enhance your data analysis skills by providing you with a comprehensive overview of the fundamentals of data analysis. You will learn how to collect, manipulate, and analyze data, as well as how to manipulate, analyze, and present it. 

What if you have the ability to interpret data and communicate your findings to others? 

Let us get started!

Skills required to be a successful Data Analyst

Machine Learning- Having a working understanding of machine learning might help you stand out during the recruitment process.

According to Statista research, a lot of investment is now being made in artificial intelligence and predictive analytics. While some may specifically work on machine learning projects, being at least somewhat familiar with the related tools and ideas may give you an edge over others. 

Cleansing of Data– It’s one of the crucial steps in developing a machine-learning model is sorting the data received from various sources and completing it correctly. It typically consumes a significant amount of any Data Analyst’s day.

Given a clean dataset, even basic algorithms may generate surprising insights. On the other side, inadequate data might lead to misleading patterns and mislead a business. Practical data cleansing skills are a requirement for Data Analyst certification, hence there needs to be a way around this.

Information Display– Data visualisation is the ability to display data results using graphics or other images. This has a single, straightforward objective: It makes it simpler to understand data-driven insights, even for people who haven’t had professional training in data analysis. Data analysts may help decision-makers in a company who might not have advanced analytical abilities by using data visualisation to help them spot trends and rapidly understand complex ideas.

With this ability, the Data Analyst can better understand the state of the organisation, communicate insightful information with team leaders, and even positively affect corporate decision-making.

Communication skills and critical thinking abilities– When you think critically, you can analyse facts, identify trends, and derive useful information and concepts. You have to work harder and make a conscious decision to think and communicate effectively. You should be able to explain your findings to others. If you are unable to communicate the patterns you see to non-technical folks, you have failed.

You should be able to converse with your educated colleagues about highly technical subjects and give succinct, high-level explanations in a way that helps rather than confuses decision-makers who are business-focused. In that case, your skills are to be developed.

Programming in statistics– Statistical programming languages like R and Python enable you to do complicated studies in ways that Excel cannot. If you know how to write programmes in these languages, you can clean, analyse, and visualise large data sets more efficiently.

Learning at least one of the two open-source languages is a good idea. Some debate exists about whether language is best for data analysis. Either language may be used to fulfil comparable data science tasks. R was developed for analytics, although Python is the more popular of the two and often simpler to learn.

Best Data Analytics Course

The availability of data-driven and technologically based tools in today’s environment has made Data Analysts’ duties simple yet varied. They are now expected to possess knowledge of the software that may be used in their daily work to improve production and support the expansion of the business. 

Anyone who wishes to work in this field should choose the greatest curriculum that can raise their overall level. There are now many data analysis courses available to encourage students to enrol in certificate programmes, improve their skills, and position themselves as more marketable candidates for jobs in this field. Imarticus offers one of the top data analytics courses. 

Their PGA course Postgraduate Program in Data Science and Analytics provides a job interview guarantee along with building up the skills needed to be successful in this domain. It aims to strengthen the basic foundation of coding and programming skills like SQL, Python, and Excel. In case, you are looking for a well-rounded analytics course, this is the one for you!

Your data analytics course might come with a Job Interview but does it offer these things?

Posted on by Imarticus Learning

Technology has revolutionized the field of data analytics. Technology has drastically changed how businesses and individuals use data to make decisions, from collecting data to analysing it. As a result, companies have recognized that having access to accurate and timely insights is vital for success in today’s competitive market. This is why pursuing a career in data analytics in 2023 could be so beneficial – you will possess highly sought-after skills by many organizations.

Data analytics allows you to gain insight into customer behaviours and preferences, helping you identify patterns and trends that can inform strategy or increase profitability. You will also be able to create reports from large volumes of structured and unstructured data, enabling decision-makers within an organization to plan for the future.

Data analytics also provides a unique opportunity to develop skills that apply to various industries, such as healthcare, finance, and retail. You can become an invaluable asset to any organisation with the right combination of technical knowledge and business acumen. Plus, the demand for data analysts is increasing – the Bureau of Labor Statistics projects that job growth in the field will increase by 28% between 2019 and 2029. This means there will be plenty of opportunities available even five years from now

Considering all of these benefits, it’s no wonder why pursuing a career in data analytics in 2023 could be so lucrative. You’ll have access to cutting-edge technology, gain valuable industry experience, and receive a competitive salary. So if you’re looking for a career path that can take you far, data analytics may be the perfect fit.

What skills does a Data Analyst need to outshine in the field?

Data Analysts need a wide range of technical and analytical skills to be successful in the field. Technical skills include knowledge of statistical software packages such as SAS, SPSS and R, database management systems like Microsoft SQL Server or Oracle, programming languages such as Python or Java, and data visualization tools like Tableau.

Analytical skills are also key for Data Analysts. These involve interpreting data effectively, identifying trends and anomalies, developing logical conclusions from quantitative information, and communicating findings easily. In addition to being technically proficient, Data Analysts should have strong problem-solving abilities, be detail oriented and possess excellent communication skills to collaborate with other team members effectively. Finally, Data Analysts should be able to work independently, prioritize tasks and manage multiple projects simultaneously.

What do you learn during a Data Analytics course and training?

A data analytics course with job interview guarantee and training will introduce various data-driven concepts, techniques, and tools. These include descriptive statistics, hypothesis testing, predictive modelling, machine learning algorithms, big data analytics and visualization.

Students in data analyst training will learn how to use industry-standard software tools like Microsoft Excel and Tableau for cleaning, preparing, analysing and visualizing data. In addition to practical skills in collecting and working with large amounts of raw data from multiple sources, students should expect to understand the underlying theories behind decision-making, problem-solving and risk assessment using statistical analysis.

Finally, PG in Data Analytics typically covers the principles of effective presentation design so that you can effectively communicate your data-driven insights to stakeholders and project teams. With the skills from a data analytics course, you will be able to identify patterns in data and make informed decisions that improve businesses and organizations.

Learn and grow with Imarticus Learning:

Advance your career in data science and analytics with Imarticus Learning, now offering a job interview guarantee program. Our comprehensive curriculum is packed with applicable content to prepare you for success – from fundamentals through complex concepts, we have you covered! And even if it’s been a while since school or programming isn’t your thing – don’t worry; we’ve got an introductory foundation module to get everyone up to speed quickly so that no one will be left behind. Don’t hesitate any longer—take the plunge into this emerging field today and employ tangible skills that are sure to make a positive impact on businesses around the globe!

Course USPs:

  • Job Interview Guarantee
  • Job-specific Curriculum
  • Live Learning Module
  • Real World Projects
  • Dedicated Career Services
  • KPMG India OE Organised Hackathons

For further details, contact the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

5 Simple Tips To Improving Your Career As a Data Scientist

Posted on by Imarticus Learning

In today’s world, most types of organised businesses use huge amounts of data to understand and analyse the needs or preferences of their prospective customers. This helps companies offer their existing clients a smooth experience with their products and services. Data science plays a vital role in this direction and provides businesses with the right tool for their activities. Notably, the number of people opting for a data scientist career these days is growing by leaps and bounds. 

Process and its Application in Business

The process of data science starts with the collection of raw data from several sources. Then, the data is prepared, i.e., filtered by eliminating unwanted content, as per the needs of the business. And then, analysis of the data starts followed by data modelling and later actual visualisation in the real system. Data science helps both online and offline businesses by capturing more and more recent data, which shall add value to the business in the long run. For example, an OTT platform service provider gathers real-time data on the choices and preferences of their clients to suggest to them the content they would be interested in. This means they help their clients get their choice’s content at their fingertips.  

This process is known as the recommendation process. The more inputs the service provider receives from a particular client, the more accurately the system may suggest him or her correct content. The better the recommendation mechanism of the service or a product, the better the satisfaction of the client. This is the reason why recently all organisations are following the process of client feedback for their products and services.

data science course

It is the job of data scientists to work out the available data and derive perfect algorithms for the system to kick-start artificial intelligence. Thus, machine learning comes hand in hand with data science and is an integral part of the total knowledge that a data scientist should possess. Considering this, the study of data science and machine learning courses in India is gaining momentum day by day.     

Tips to Improve Your Career as a Data Scientist 

The simple tips that will help to improve your career as a data scientist are as follows – 

  • Starting a career in data science is equivalent to breaking into software engineering for someone, who does not exactly have the same background but the basic intelligence, passion and skills to crack the processes. It may be safely mentioned that a candidate may be from any background i.e. science, humanities or commerce and may still pursue a career in data science. However, it may be noted that the candidate must possess good reasoning skills and a steady aptitude to learn quickly and efficiently.
  • Even a prospective candidate without prior programming language knowledge can be a very good data scientist in future provided the candidate follows the subject on the right platform. The candidate must enrol himself or herself in an eminent institute, having a huge experience in mentoring on the subject.
  • It may be noted in this context that though the study of data science involves enormous learning procedures, one should not be too much stuck in theory but rely on practice when he or she has completed the course. It is more of a practical or hands-on job and hence, preparing and running a model is more important than anything else.
  • A budding data scientist must have excellent mentors. We must remember that this is a newly evolving field and hence, getting oneself updated with the latest domain knowledge will be extremely helpful to one’s career. This is exactly where the role of good institutions comes to play.
  • The prospective candidate should choose the correct industry, in which the candidate has an inherent interest. It may be in SCM (supply chain management) or even finance. The course to be chosen should also be guided by keeping the basic interest of the candidate in mind. Good institutions have career counselling coaches who can understand the ability and interests of a particular candidate and may guide the candidate accordingly.

Conclusion 

A career as a data scientist is highly rewarding for a prospective candidate provided he/she has a grasp of the subject precisely and applies the knowledge in the industry domain according to his/her interest. The pay package of a data scientist depends on the skills and knowledge the candidate has mastered and the number of successful project models that have been delivered. The IIT Roorkee data science and machine learning course at Imarticus is an online training programme for five months. This course will guide you on how to become a successful data scientist and help you to achieve your dream. 

Deep learning: Why it matters for the future

Posted on by Imarticus Learning

The leaps and bounds that technology has taken since artificial intelligence’s inception in the 1950s are impressive. And it happened in the absence of the internet. Experts in the period between 1957 to 1974 derived the proof of principle for AI. They visualised a system that could recognise spoken language with the help of data processing. This technology has grown exponentially to reach the era of “big data.” This is where a large amount of data is processed in minutes. The future of AI looks promising. From translating languages in real-time to self-driven cars, it’s everywhere. A PG in Data Analytics helps you start a successful career in this promising field.

The following section will help you explore the scope of Deep Learning in the future.

Importance of Deep Learning for the Future through Examples

data analytics course

Almost all companies in the world are leveraging AI and ML-based machines. So, knowing how this technology is being used is important. The examples listed below discuss Deep Learning implementation in real-world scenarios. We also explore the scope of future improvements in DL-based technologies. This will help you understand the need for a Deep Learning course in the future.

Machine Translation: Assistants like Siri, Google Assistant, and Alexa have changed our mundane routine around the globe. These assistants are trained using Deep Learning algorithms to generate the fastest and the most appropriate responses to human queries. They translate spoken language to machine language to process natural language instantly.

Additionally, assistants and software like Google Translate perform another type of machine translation. They efficiently translate the words spoken by a person in one language into another in real-time. In the future, this technology will improve multifold to translate more than one language as the speakers speak. If you are a technology enthusiast, get a PG in Data Analytics now! You can be a part of the ongoing technology revolution.

Mobile AI: Several AI-based applications are available in the market today. However, the lack of computing space and memory in mobile phones stops this technology from reaching larger audiences. In the future, most of us will leverage deep compression technology to reduce the size of applications. These applications could be developed for laptops, tablets, or phones.

Research: Deep Learning is not only for delivering comfort and luxury. It also delivers on bigger responsibilities like saving lives. Medical researchers have teamed up with IT professionals to create systems for detecting life-threatening cells (cancerous) in the human body. We have indeed used diagnostic systems assisted by computers for a long time. But the introduction of deep learning has changed the game in medicine.

Data processing is used for detecting hazardous cells in the human body. However, many challenges in this field are yet to be solved. Hundreds of medical imaging devices generate images based on varying principles. Technology has not developed at a pace to understand this level of variation. You can join the healthcare field with a PG in Data Analytics.

Employee Retention: Companies are bombarded with large volumes of employee data that require daily processing. To retain employees by providing the best satisfaction level, companies’ HR department must link their employee information with different categories. These categories are compensation management, onboarding procedures, and incentive management. In the future, Deep Learning can be paired with blockchain to get better results. Also, the process of training and employee reviews could be automated using Deep Learning. A Deep Learning course can help you understand the new HR-related tools. Most of them are AI and DL based.

Customer Support: Today, this technology is used to improve the performance of chatbots. They work with inputs from words, audio, images, and videos to generate the desired output. In the coming years, this technology will expand its scope to include various facets of customer support. You can check out the Data Analytics course with placement options. This would help you set foot in the field fast.

Defence: The Defence ministries of many countries are leveraging deep learning to detect hazardous and safe areas for their naval, air, and ground soldiers. In the coming years, these algorithms can diversify to automate the responses of missile systems against an incoming threat.

Kickstart your career with a Data Analytics course with Placement opportunities

The knowledge of Deep Learning or neural networks can help you explore a career in various IT roles. These include the positions of Data Engineer, Software Developer, Research Analyst, Bio Information, and Data Engineer. Generally, Machine Learning and Deep Learning come under the umbrella term of Artificial Intelligence (AI). According to the study by The International Data Corporation, the financial value of AI is expected to reach $7.8 billion. Imarticus Learning offers a job-ready Data Analytics Course with placement for fresh graduates and professionals with 0-5 years of experience.

Imarticus Learning offers a job-ready curriculum for fresh graduates and professionals early in their careers. You can learn more about the PG In Data Analytics program on the official website. Call their professional support, or use chatbots to resolve your queries.

Does your machine learning course offer these features?

Posted on by Imarticus Learning

Are you considering taking a machine learning course to level up your skillset? It is essential to make sure that the course you choose is comprehensive and provides tools that are easy to understand. 

Whether you want an introductory crash course or an in-depth, hands-on course with practical takeaways, there are certain features every good machine learning class should have. 

In this blog post, we’ll examine key elements of a quality machine learning course so you can make sure it fulfills all your educational needs.

The fundamentals of machine learning

artificial intelligence and machine learning courses

First, a great machine learning course should give students an understanding of ML algorithms and techniques fundamentals. This includes supervised and unsupervised learning, hyperparameter tuning, feature engineering, and more. It should also provide an overview of popular ML libraries such as TensorFlow, Scikit-Learn, Keras, PyTorch, and others. A solid foundation in ML basics will ensure students have the knowledge they need to become well-rounded practitioners. 

Projects & Applications 

A good ML course should also include hands-on projects that help students apply their knowledge of ML techniques in real-world scenarios. Projects can consist of image recognition applications using convolutional neural networks or natural language processing tasks using recurrent neural networks. By working through these projects, students can gain valuable experience that they cannot teach in the classroom alone. 

Tools & Resources 

A quality machine learning course should provide access to helpful tools and resources to aid their learning process. For example, many courses offer access to cloud computing platforms such as Google Cloud Platform or Amazon Web Services, which allow students to run experiments on powerful machines with minimal effort. Additionally, some courses even offer access to GPU instances so that students can significantly speed up their training time. All of these tools are invaluable when it comes to mastering ML concepts quickly and efficiently.    

Real-World Examples

An excellent machine learning course should have plenty of real-world examples so students can better understand how their learning concepts apply to everyday life. After all, what good is knowing the theory if you can’t use it in practice? Real-world examples also help students think more creatively about solving problems and give them the confidence to tackle new challenges. 

Interactive Exercises

An excellent machine-learning course should offer interactive exercises that allow students to test their knowledge and understand how different concepts interact. This helps build critical thinking skills and will enable students to learn from mistakes. Plus, these exercises are usually fun, making them more engaging for students than just reading textbooks or watching lectures. 

Course Support

 Students need to know they have support available if they get stuck on a problem or need help understanding something. An excellent machine learning course should provide online and offline access to resources such as tutorials, forums, mentors, and more so that students can get help when they need it most. 

With so many options for machine learning courses, it can take time to decide which is best for you. To make sure you get the most out of your educational experience, take the time to research each course carefully before making your decision. Make sure it covers all the basics and provides hands-on projects and access to helpful tools and resources—then you will know you’ve got yourself a winner!

Discover IIT artificial intelligence and machine learning course with Imarticus Learning.

Ready to take your career in a new technology-focused direction? Enroll at the E & ICT Academy for their comprehensive IIT AI ML course! Equip yourself with all you need for revolutionary leadership – don’t hesitate, start your journey now!

 Course Benefits For Learners:

  • Students work on 25 real-world projects to develop real-world business experience and prepare for a rewarding data science career. 
  • With a certificate recognized by the E & ICT Academy, IIT Guwahati, and a credential supported by Imarticus Learning, students, can attract employers’ attention and demonstrate their skills. 
  • Students who complete these AI and machine learning courses land lucrative jobs in the machine learning and artificial intelligence sectors.

 Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via the chat support system.

A comprehensive guide on how to build a neural network: Python for beginners

Posted on by Imarticus Learning

Neural networks are systems that operate similarly to the human brain. Currently, neural networks are used daily – even without us realizing it. For example, when we use our mobile assistant to perform a search- such as Siri, Google, or Amazon Web- it is all neural-network driven. In computer games, neural networks are also utilized – such as how the system adjusts its players, maps applications, processes map images, and finds the shortest routes to reach the destination.

Neural networks can perform any of the following tasks:

Translate text

Control robots

Recognize speech

Read handwritten text

Identify faces

How does the Neural Network Function?

There are three different layers to neural networks:

Input layer: Picks up the input signals and passes them on to the subsequent layers.

Hidden layer: This layer does every feature extraction and calculation required. Often, we will find more than one hidden layer in a single neural network.

Output layer: This is the final layer and has the job of delivering the result

best data analytics course

To better understand these layers and their workings, let’s take a real-life example of how traffic cameras capture the license plates of vehicles speeding on the road. Pixels, which make up the picture, are fed into the input layer in arrays. Each neuron has activation, or an assigned number, ranging from 0 to 1. For the white pixel, it is 1, and for the black, it is 0. Next, the input layer passes these inputs to the hidden layer. All the interconnections have weights assigned to them randomly, which then is multiplied by the input signal. Lastly, a bias is added to all these weights.

The weighted addition of the inputs is then converted to the information of the activation function- this function decides which nodes should fire for the feature extraction.

Here we will take a look at the different types of activation functions that are there:

Threshold function: This function is deployed when we don’t want to worry about mid-level uncertainty.

Sigmoid function: The sigmoid function is useful when the model is required to predict probability.

Hyperbolic Tangent function: This function is very similar to the sigmoid function; however, it ranges from -1 to 1.

ReLU (rectified linear unit) function: This rectified linear unit (ReLU) function works in such a manner that it gives the function value, however, if the value is over 1, then it will just be one, and similarly, if the value is less than 0, it will be just 0. This ReLU function is the most commonly used among all.

Now that we know all the activation function types, let’s explore more neural networks. So finally, the model, after having applied a suitable application function to the output layer, will predict what the outcome is. The error rate in the output is minimized through the adjustment of weights, and the error itself is back-propagated through the network. The weights are constantly adjusted until they perfectly fit all the training models that it has been put in. Furthermore, the output is contrasted with the original result, and numerous iterations are done to attain maximum accuracy.

Neural Networks and their Types

There are mainly six different types of neural networks, as discussed below:

Feed-forward neural network: This is the example we just explored where data travels in a uni-directional manner- from input to output. It is also the simplest form of artificial neural network.

Radial basis function neural network: Here, the data point is classified based on distance from any central point. We often want to group things and contract a centre point when we don’t have any other training data. This network groups similar data points and has its application in power restoration systems.

Kohonen Self-organizing Neural Network: Discrete maps that are comprised of neurons have inputs that are vectors of random input. Applications of this network include recognizing patterns in data such as medical analysis.

Recurrent Neural Network: Here, the hidden layer saves the output such that it becomes part of the new output and can be used for future predictions.

Convolution Neural Network: Here, the input features are filtered and taken in batches, therefore, allowing the network to remember an image.

Modular Neural Network: This model consists of multiple neural networks which function together to get an output.

Keras is an efficient software that allows users to create artificial neural networks with the Python programming language. Many data scientists use Python because it is essential for the Keras software. If you are new to Python and data science, you can opt for a Data Science and Analytics course or data analyst training to learn how to use Python more efficiently.

Aspirants in this Data Science and Analytics domain can benefit significantly by enrolling in the Post-graduate Program in the Data science and analytics course of IMARTICUS Learning.

Data Scientist Careers: What You Should Know Now

Posted on by Imarticus Learning

Scientific usage of gathered and filtered information for extrapolating the outcome of an unknown (future) situation by using different tools and languages before presenting the data in a visually ready reckoning format for influencing business decisions is called data science. This process consists of two main tasks – exploratory data analysis and data engineering. Other related activities such as data visualisation, data analytics, model creation and model deployment complete the entire cycle and the entire gamut of activities which fall under data science.

Career Guidelines

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The Data Scientist career is arguably the fastest-growing career in the software world and is not just meant for candidates who have a Bachelor’s degree in Software Engineering or Computer Science Engineering. Study on data science also includes artificial intelligence, machine learning and deep learning in the course. However, certain key skills and know-how are required before taking data science as a career option. Some basic guidelines for such aspiring candidates from the non-core or non-technical subjects or domains are as follows –

  • It may be noted that the activity of a Data Scientist on one platform is very different from that of another. So, a prospective candidate has to figure out the course that the candidate is interested in and is capable of handling. The candidate must learn the skill of data collection by reading articles or videos and develop the habit of recording information by taking notes.
  • Making friends in the data science community before taking a deep dive into this field is also another useful idea. Community discussions unravel many unknown facts and may help the aspiring Data Scientist to come across a solution. Besides, they may continually be aware of the best practices in the subject domain and come across leaders in this field, who have already tasted success, albeit from a different field.
  • A Data Scientist must be in the habit of upgrading his or her knowledge by studying the latest research papers or new tools, languages and algorithms that are being published from time to time. The constant inquisitiveness regarding the updated knowledge will help the candidate to scale more heights.

Career Options

Data science and machine learning courses in India result in highly rewarding careers. However, it may be noted that the application of data science is industry-specific and hence the knowledge of a Data Scientist is a bit incomplete until and unless he becomes a domain expert. The different jobs that a prospective candidate may hit upon after completing the course are as follows –

  1. Data Analyst – This is the beginner’s role that a candidate lands upon just after completing the course. The basic functions of this position are to gather raw data, clean them and apply algorithms to it by the usage of statistics and other tools. Besides, they have to be masters in PPT and other tools that are used for presentations. A business house takes decisions after they review its inputs.
  1. Data Scientist – The role of a Data Scientist is a consultant’s role and oversees the activities of a Data Analyst along with other important functions like model creation, implementation and testing. A Data Scientist, who is also an expert in domain knowledge, is an asset to the organisation. The models that he creates are more practical and expected to yield far more accurate future predictions. It is the role of a Data Scientist to derive the key performance indicators of an organisation.   
  1. Business Analyst – A Data Scientist with a strong interest in business development predictions and ample domain knowledge often chooses the career of a Business Analyst. However, in this case, it may be noted that he must also possess operational knowledge along with the past and present practical challenges faced by the business. It’s noteworthy to mention here that a Business Analyst can also extract the key performance indicators of a company.
  1. Statisticians – The role of the Statisticians is to collect and organise data in a way that a trend is visible through the interpretation of those data. The sole purpose is to make a business decision. They also play an immense role in advising on long-term organisational strategies. 
  1. Financial Analyst – A candidate coming from a finance background and foraying into the field of data science often chooses this portfolio. This position is of diverse nature and finds roles in banks, NBFCs and corporate, as well. We may find them as a Credit Analyst or a Financial Model Developer.
  1. Machine Learning Engineer – Machine Learning Engineers provide software solutions through clean data funnels. Strong statistics and programming skills coupled with software knowledge are their basic assets. They also run tests and experiments on the different models they create.

Conclusion

Data science has already picked up its growth trajectory in India, exponentially, and it has the potential to double the industry volume just within a couple of years. The IIT Roorkee data science and machine learning course at Imarticus is an online course. The duration of the course is 5 months. It is one of the best data science courses in India that will help you to achieve your dream.