Best Data Analytics courses in India - Finance, Tech & Analytics Career Resources

Beat the market: Learn Computer Vision in Python

Posted on February 9, 2022March 28, 2024 by Imarticus Learning

Are you looking to learn a new skill that can give you an edge over your competition? If so, then you should consider learning computer vision with Python. This powerful programming language has become increasingly popular in recent years and is perfect for tackling complex computer vision tasks.

This blog post will discuss computer vision and learn it using Python. We will also provide a few resources to get you started!

According to the World Economic Forum, nearly half of all jobs will get replaced by automation within the next 20 years. To stay relevant in this speedily changing world, we must learn new skills that can help us adapt and succeed.

One such skill is computer vision which allows you to teach computers to see as humans do! It’s an excellent process to stand out from the crowd, and you can use it in various industries such as security, manufacturing, healthcare, and more.

What is computer vision?

It is a field of AI that trains machines to understand the content of digital images or videos. You can do it by using algorithms, machine learning techniques, and deep learning networks to identify objects in an image or video frame.

With Python programming language, it’s possible to create programs quickly without having profound knowledge about computer vision algorithms or models.

Tips to get started with computer vision in Python

There are many different ways to get started with computer vision in Python.

OpenCV library:

The OpenCV library is a popular choice for working with computer vision in Python. It provides a wide range of functions that allow you to efficiently perform tasks such as object detection and feature extraction from images or video streams.

Scikit-learn library:

The Scikit-learn library is another popular choice for working with computer vision in Python. It provides a range of algorithms for performing image classification, object detection, and regression analysis tasks.

Keras library:

The Keras library is another popular choice for working with computer vision in Python. It provides a high-level neural networks API, making it easy to build and train deep learning models.

Tensorflow library:

The Tensorflow library is another popular choice for Python computer vision. Python’s high-level programming language provides an API for building and training neural networks.

Matplotlib library:

The Matplotlib library is another popular choice for working with computer vision in Python. It provides a high-level API for creating charts and graphs using the Matplotlib library is another popular choice for working with computer vision in Python.

Discover AIML Course with Imarticus Learning

The Artificial Intelligence and Machine Learning certification collaborate with industry professionals to deliver the most satisfactory learning experience for aspiring AIML students.

This intensive Python certification will prepare the student for a data scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

Course Benefits For Learners:

This Supervised Learning course will help students improve their Artificial Intelligence basic abilities.
Students can take advantage of our Expert Mentorship program to learn about AIML in a practical setting.
Impress employers and demonstrate their AI talents with a Supervised Learning certification supported by India’s most famous academic collaborations.
This course will help students gain access to attractive professional prospects in Artificial Intelligence and Machine Learning.

Marketing of the Future: How Data Analytics is Changing

Posted on September 27, 2021January 24, 2022 by Imarticus Learning

The corporate industry is ever-evolving, and even more so when it comes to data analytics. From standard out-of-the-box reports to a tool operated by digital mediums, it has come a long way. In the past, it was mostly a way to decipher and keep records of bygone trends, but now it has turned into a tool that helps you predict future trends.

It even helps you understand your target customer better through their online habits. And as daily life gets more and more virtual-oriented, the need for machine learning and AI-oriented data analytics will keep growing. So will grow the number of positions for good data analysts.

Here, you have a chance to learn data analytics with Imarticus Learning’s new PG program to enhance your skills to the max.

Coming back to the evolution of data analytics throughout the years, there are a few major changes that need to be addressed. Such as the shift to digital analytics from standard reports, as well as live AI reports and alerts.

Digital Analytics from standard reports

The major difference that has gained traction in the last few years would be how virtualized the data analytics industry has become. In the past, most of the analysis process was done through tool-generated out-of-the-box reports which today are almost out of date. Now the main focus has shifted towards reading the targeted customer’s habits and needs and forming strategies to cater directly to it.

It becomes a lot less hassling on both parts as instead of guessing you’re actually finding out what your client needs and providing solutions for it. Now with the change in how data is extracted and processed the job of an analyst has also evolved. This is one of the reasons why data analytics courses in India have been getting more and more popular in recent years.

Live AI reports and alerts

Another system that has become immensely popular is live AI reports that alert the clients to any ups and downs in trends. This helps them to develop quick strategies to respond to the changing trends. Not just that, the sources from which data is generated have changed drastically. Not just real-time market trends, data today can be sourced from online retails, social media, intelligence tools as well as pop-ups and advertising platforms.

The bandwidth of data has increased and along with it, the variety, responsibility, and positions of a data analyst job. As this process evolves more the scopes will increase even more in numbers. This is a good time to enhance your skills if you are thinking about career prospects. There are many institutes that offer good data analytics courses in India that might suit your preference. However, there are few things you should keep in mind when it comes to data analytics:

Many companies are venturing into exploring open-source software, but the majority is still using business analytics tools and visual analytics.
Data analysis has become a part of our daily lives. As a result, new and faster ways to generate data are coming out that need higher levels of skills.
The industry is constantly evolving, so it is necessary to always be top of your game as a data analyst.

Conclusion

Data analytics is one of the careers that has a firm base. More and more opportunities are going to open up in the future. This might be a good time to learn data analytics with a proper PG program that will help your career bloom.

Imarticus Learning: Fuelling India’s Data Analytics Workforce

Posted on September 22, 2021March 22, 2024 by Imarticus Learning

What is Data Analytics?

Data Analytics involves analyzing raw data and drawing meaningful conclusions and patterns from that data. In data analytics, a lot of processes are automated to eliminate manual intervention. You can take up a data analytics course to understand the intricacies of the subject.

In data analytics, a lot of algorithms are prepared to make the job easy. These days you can take up a data analytics course with placement. A data analytics certification course makes you credible enough for the job.

Understanding Data Analytics

Data Analytics can be complex when you try to understand it. A data analytics certification course can help you know what the subject entails and how to make the best use of it. The data analytics course will also introduce you to the world of algorithms.

Data Analytics is a broad subject that includes several diverse types of data analysis techniques.

Data Analytics can be used to mine different kinds of data insights. These insights can be used in improving processes and transforming them for the convenience of the data users. You can take up a data analytics course with placement to practically apply these algorithms and techniques of data sorting and data analysis.

Companies like Imarticus Learning are tirelessly working towards making the Indian workforce tech-savvy and well-versed with data analytics and its application. If more and more workforce joins hands with Imarticus to learn data analytics, the workforce will become digitally enabled to deal with a large amount of data. They would know how the data would be put to proper use.

Use Cases of Data Analytics

Data Analytics training can be used to understand several trends that dominate the market. You can apply predictive analysis using the insights from these data points. Several industries are now making use of data analytics to optimize their processes.

For instance, in the manufacturing industry, data analytics is used to store and record runtime, work queue, and downtime of all the machines in the factory. The data can then be utilized to optimize all the processes and to make manufacturing better.

However, data analytics is not limited to spotting bottlenecks in the process. It can do much more. It can make the entire process better and more efficient. You can also use data analytics to speed up the manufacturing process as a whole, as with data analytics, you can reduce the waste to a great extent.

Types of Data Analytics

If the workforce knows how to use Data Analytics, they will be able to use technology better. Some of the types of Data Analytics are:

Descriptive Analytics: This is used to understand what has happened over a while.
Diagnostic Analytics: If something happens, you can analyze what went wrong using diagnostic analytics.
Predictive Analytics: In the case of predictive analytics, the algorithms are used to predict a future trend.
Prescriptive Analytics: These algorithms are used to take a suggestive measure for any action.

Conclusion

Building an analytics workforce is the need of the hour. Therefore, it is essential to train more professionals and prepare them for the analytics world. Digital literacy is very important to automate functions, and data analytics is an integral part of it.

Imarticus is on a spree to enable people to use data analytics to decode patterns and understand data. Imarticus has several courses on data analytics. You can enroll in all of these courses to get an in-depth insight into how data analytics works and make the best use of it. The certifications from Imarticus have a great value in the industry.

Most Essential Asset for Professionals: Data Analytics Tools!

Posted on September 3, 2021March 22, 2024 by Imarticus Learning

To perform data analysis, professionals use tools & software that ensure the best results. There are many of them in the market, but a few are on the top list for data analysts that need to be chosen wisely to extract the best benefit.

This article discovers the best data analyst tools and highlights key features of each based on different types of analysis processes. But first, here’s a basic definition & introduction.

What Are Data Analyst Tools?

Data analyst tools are applications & software that data analysts develop & perform analytical processes to make better, informed business decisions while keeping costs low & profits high.

Top Tools Used by Data Analysts?

1. Business Intelligence Tools

BI tools are the most represented means to perform data analysis. Specialized in business analytics, they prove beneficial for every data analyst to monitor, analyze, and report essential findings. Self-service, advanced SQL modes, and predictive analytics make them easily adjustable to every level of knowledge without immense IT involvement.

DATAPINE covers most requirements from beginners & advanced users.

Key Features:

Visual drag-&-drop interface
Powerful predictive analytics & interactive charts & dashboards
Intelligent alarms triggered for anomaly

2. Statistical Analysis Tools

There exist multiple programming languages that make work easier & effective. With the expansion of languages, some rules and scenarios need special attention for statistical data analysis & modeling.

R PROGRAMMING is the most popular tool for data analysts.

Key Features:

An ecosystem of more than 10k packages & extensions for data analysis
Statistical analysis, modeling, & hypothesis testing
Active community of researchers, statisticians, & scientists

3. General-Purpose Programming Languages

Programming languages help to resolve a variety of data problems. Tools like C#, Java, PHP, Julia, Ruby, and Python are many reliable solutions.

PYTHON is the most trusted tool.

Key Features:

Open-source solution with simple coding processes
Easy integration with other languages
Advanced analysis processes through ML & text mining

4. SQL Consoles

SQL is a programming language used to manage data held in relational databases, effectively handling structured data for analysts. Highly popular in the data science community, these tools are used in various business cases & data scenarios.

MYSQL WORKBENCH is the most popular one.

Key Features:

Unified visual tool for data modeling, administration, SQL development, backup, etc.
Instant access to the database via Object Browser
SQL Editor offers color syntax highlighting, reuse of SQL snippets, & execution history

5. Unique Predictive Analytics Tools

Predictive analytics is an advanced technique to combine data mining, AI/ML, and predictive modeling to predict future events. It is an essential data analysis tool as it simplifies predictive analytics processes.

SAS FORECASTING is an analysis software helpful for predictive analytics processes & helps analysts to predict future scenarios.

Key Features:

Automatic forecasting for entities or products, including hierarchical forecasting
Scalability & modeling to create an ensemble
An unlimited model repository including time-series & casual methods

Apart from the tools mentioned above, there are industry-specific analytics tools & data science platforms that assist professionals. A business analytics course can help you better understand what data analytics is!

Build New-Age Career with Imarticus:

Imarticus Learning offers Data Science Courses, the most extensive, industry-approved experiential learning program ideal for Data Analysts.

Industry experts have developed the programs to help students learn real-world applications of Data Science from scratch & build robust models to generate valuable business insights and predictions.

Take a giant career leap with this analytics program.

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

Customer Data Mapping, Engagement and Developing Trust with Data Analytics!

Posted on August 11, 2021March 29, 2024 by Imarticus Learning

Data analytics is the new talk of the town. You might be planning to learn something online and wondering if you should do a data analytics course or a certification in data analytics, then this article will tell you the reasons to learn data analytics online and how in every business sector data analytics is getting more relevant every day.

To ensure the success of any business, developing trust and ensuring customer satisfaction has always been a key recipe. The introduction of analytics in customer data mapping has completely transformed the way businesses engage with their customers and win their trust.

With proper customer data utilization using analytics, businesses are able to engage customers in a more personalized way. Many organizations are reaping the benefit of using analytics to improve customer engagement. Analytics allow using intelligence in the customer data to provide tailor-made offerings. Several factors like using various data sources, well-developed core analytics capabilities and integration of AI and IoT into processes make this possible.

Key trends in customer engagement using analytics:

Growth is likely to continue:

More companies have started using analytics for better customer satisfaction, and this percentage is growing each year.

Analytics going to be the main driving force:

This has been observed that organizations that are more experienced in using analytics than their competitors are able to gain more trust and provide more customer satisfaction.

Analytically experienced are using more data:

Analytically experienced organizations tend to use more data from all possible sources when compared to lesser experienced organizations.

Data sources, like customer, vendor, regulator, and competitor data, and data types, like mobile, social, and public data, all are getting used and playing a major role.

Key points for better customer mapping

Data source and data types:

Large in volume and variation ensures quality data. When different types of data like mobile, social, and public data are collected from various sources like customers, vendors, regulators, and competitors, analytics can lead you to a more accurate forecast.

Integrated system:

By using the data-based dashboard while fixing your customer strategy, the scope of guesswork comes down to null. Data analytics systems integrate into existing infrastructure with minimal effort and without a need for overall change. Integrating new data and analytics into the existing model improves your customer service.

Innovation to turn customer mapping into customer satisfaction

Data mapping using analytics takes traditional data mapping to a whole new level. This works as the best foundation for decision-making. These strategic changes could include social media strategy, website upgrades, and many other things.

Building profiles using Analytics

Analytics helps to identify each client independently, based on their intercommunications throughout their journey with the business. Businesses can then trace and gather precious data for future use. Analytics can build individual customer profiles using this data based on real-time action, habits, and inclinations.

Importance of Qualitative data

Few analytical tools support solutions that take qualitative data into account. Knowing how happy customers are, key phrases they use, or survey feedback are all forms of qualitative data. Quantitative data analytics and qualitative customer experiences must be equally prioritized to ensure a better result.

Prioritization of personalization

Incorporating customer journey analytics into strategy is important. Using analytics, the appeased customer is going to receive can be personalized and segmented. When customers receive more personalized and relevant content, they are likely to be more interested.

Conclusion

If you want to learn data analytics online, then Imarticus offers you a data analytics course and certification in a data analytics program that you might be interested in.

Mapping customer data, understanding the buyer’s persona (a fictional identity of a buyer based on customer data), and going the extra mile to meet the customer’s demands can really help businesses, and data analytics is the way to go.

Keen To Develop A Solution That Will Predict User’s Online Training? Imarticus Could Help You Develop The Right Expertise

Posted on July 28, 2021March 21, 2024 by Imarticus Learning

Online user behavior is something e-commerce and target marketing has been relying on. What helps them predict online user behavior is machine learning and Artificial Intelligence.

The user interest and the pertaining trend help the business and marketing team to anticipate the changes and take the necessary steps for improvement. This change is a trendsetter that has urged many other fields to use the same mechanisms to study its users.

Ever since the online training process gained popularity finding out what the users’ needs became crucial to set up the right kind of courses and setting up the ideal curriculum to nourish their careers.

Predicting user’s online training

Getting the correct feedback on the online learning process is significant to know about what the users are interested in. It helps refine the curriculum and also helps introduce more useful courses to increase the chances of a better career.

Predicting a user’s online training interest requires some specific expertise but it doesn’t involve a single field of study. It requires a collection of subjects that are part of data science. In order to be an expert in predicting user interests, these are the fields of technology that one must master.

Artificial Intelligence: User prediction using AI is done through developing models and algorithms that provide a predictive outcome. It is also one of the primary objectives of this technology.
Machine Learning: ML is the branch of AI that helps with the computational part or where the machines are made intelligent to work like human brains. BY processing the machines one can help find the relevant data to create a reliable predictive analysis to find out the user interest.
Deep Learning is that part of AI that functions as human brains where it recognizes speech, language, objects, etc and that also helps in decision making. Using these factors creates a prediction model that has near-accurate validity. In fact, it is one of the most popular careers at the moment.
Natural Language Processor NLP is using technology to understand the common and natural language used by humans. It involves compiling data and processing it appropriately through mathematical, linguistic, or statistical methods. It is just a collective term for multiple steps. Moreover, it uses most of the above mentioned technologies as well.
Computer Vision is another branch that works on perspective analysis using videos and images. They help with replicating the visual system in humans and automate the tasks accordingly.

How Imarticus helps?

Imarticus offers various courses in Artificial Intelligence that includes Deep Learning, Machine Learning, Natural Language Process, Computer Vision, etc in the curriculum. It makes a foundation for predictive analytics. The course duration ranges from 2-8 months depending upon the user’s choice. Both online and classroom options are available for most courses.

Analytics and Artificial Intelligence courses are open to both freshers and working professionals. They can select the relevant option when opting for the course. The courses are termed PG-courses and Pro-Degree courses respectively.

Keeping in mind the time constraints for the professionals, the pro degree courses may be completed in a shorter span of time.

Not only do they provide quality courses but also provide opportunities to work with giants such as IBM and others. Both types of courses have this partnership option for hands-on experience.

Such hands-on courses enable the users to polish their knowledge and make them borderline experts in their respective fields, even for an entry-level.

Conclusion

The learning process at Imarticus includes a program mentor who gives proper guidance and support for the academics. Moreover, the placement assistance at the end of the course increases the prospects of landing the right job.

Unlocking The Future of Financial Analysis with Advanced Analytics!

Posted on July 26, 2021March 22, 2024 by Imarticus Learning

Advanced analytics involves using advanced methodologies like data science, data set analysis, and automation processes to understand business trends. It is no surprise that advanced analytics is changing the landscape of business as we know it. But, how is it doing so?

This article will help you find the answer to this question and more. The following points will cover advanced analytics, its relationship with financial analysis, and how to learn financial analysis

What is Advanced Analytics?

Advanced analytics uses statistical methods, predictive modeling, process automation, and machine learning (ML) techniques that are well ahead of conventional business intelligence tools to analyze the required data. Advanced analytics employs data science and its sophistical techniques of analysis to forecast future trends and predict the probability of potential occurrences.

Simple analytics and BI can only give a snapshot of an organization. On the other hand, advanced analytics allows you to predict future trends or the most probable outcomes of a business decision. It equips you with a wider range of capabilities so you can overcome the issues present in conventional analytics.

How Advanced Analytics Enhance Financial Analysis?

Advanced analytics expands on the technologies and techniques used in business intelligence and analytics by incorporating more sophisticated methods. It can improve any implementation of analytics including financial analysis. Some of its prominent applications in the financial sector are:

Automating financial analytics

Financial analytics consists of many procedures such as creating datasets and updating the existing ones. It also involves data collection and generating reports. Advanced analytics training can help in automating all of these procedures.

By using advanced analytics, you can build datasets that can update their macroeconomic data automatically. This includes inflation, basic interest rate, and other data points. Similarly, it can help you collect data from financial statements automatically by using APIs.

Making predictions

Financial forecasting is a major aspect of financial analytics. Companies rely on it to make crucial decisions, evaluate risk, and analyze investments. Advanced analytics utilizes machine learning models that can help you perform predictive analysis.

You can build models that can adapt to the changes in financial and economic domains automatically and can make recommendations based on their insights to help in decision making.

Advanced analytics improves the data collection process by using more sources and completing the task much quicker.

Optimize current implementations

Using advanced analytics can help businesses improve the efficiency of many of their processes. It allows them to automate multiple procedures which require staff and time. Automated tasks have fewer chances of making mistakes as machines do not get fatigued. Companies can allocate the time and resources saved by all of this in other areas that require more attention.

How to Learn Financial Analysis?

Financial analysis has many applications for advanced analytics. The field is ripe with opportunity and the technology is relatively new. It allows companies to get ahead of their competitors and become a leader. Due to these reasons, the demand for a skilled financial analyst who is familiar with advanced analytics implementations is exponentially high.

The most effective and efficient method to become a financial analyst is by taking a financial analyst course. A financial analyst course will help you learn the skills required to become a professional in this field and get certified. It offers a structured curriculum so you can learn the subjects in a timely manner and plan your studies accordingly.

Taking a course will help you stand out from your peers and become a preferred candidate for financial analysis roles.

Financial analytics is a broad sector and the rising popularity of advanced analytics is transforming this field considerably. If you are interested in becoming a financial analytics professional, you must have a strong grasp of advanced analytics. It would help you boost your career growth.