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Tag: Data science online training

Why is Data Cleaning Essential

Posted on by Imarticus Learning

Businesses rely largely on relevant data to make effective decisions and forecasts. Poor data hygiene maintenance is a reoccurring issue for organisations all around the world. It can not only stymie productivity but also lead to increased maintenance costs and system breakdowns. According to a recent market analysis conducted by IBM, poor data hygiene costs the US economy $3.1 trillion every year. 

This is where the role of data cleansing comes in. Data cleansing helps eliminate “dirty data” and guarantees that the outcomes of data analysis are accurate, dependable, and trustworthy. In this article, you will learn more about the importance of data cleaning, the numerous tools involved in the process, and why taking up a data science and machine learning course can be a beneficial career choice. 

What is Data Cleansing?

Data Science Course

Data cleaning, also known as data cleansing or data scrubbing, is the process of identifying and correcting or removing errors, inconsistencies, inaccuracies, and duplications in datasets.

It is an essential step in the data preparation process and plays a crucial role in ensuring the accuracy, reliability, and integrity of data. 

Data cleansing is often conducted using data cleaning tools, software, or computer languages that automate the process, but depending on the complexity and sensitivity of the data, it may also entail manual inspection and validation.

Effective data cleansing ensures that data is precise, credible, and consistent, which is essential for facilitating reliable insights, making educated decisions, and driving business growth. 

Benefits of Data Cleansing

Having clean data ultimately increases overall productivity and allows for the highest quality information to streamline decision-making. Here are some of the other reasons why data cleaning is essential in facilitating business growth:-

  • Accurate and Reliable Data: Clean data is required for facilitating accurate and dependable analysis, reporting, and data-driven decision-making. Flaws, inconsistencies, and inaccuracies in data can result in wrong insights, inaccurate conclusions, and poor decision-making, all of which can have serious implications for businesses and organisations.
  • Data Consistency: Data cleansing helps to assure data consistency across multiple sources, systems, and formats. Inconsistent data can cause confusion, misalignment, and misunderstanding of data making it difficult to efficiently compare, integrate, and analyse data.
  • Data Integrity: Clean data is devoid of duplications, missing numbers, and other data quality concerns, so it retains its integrity. Data integrity is critical for ensuring data dependability which is vital in regulated areas like banking, compliance, and healthcare.
  • Enhanced Data Quality: Data cleaning helps to enhance the overall quality of data  by identifying and resolving mistakes, discrepancies, and errors. High-quality data is critical for creating credible insights and driving crucial business decisions.
  • Reducing Unnecessary Costs: Data inaccuracies, replication, and discrepancies can cause firms to incur needless expenditures. Data cleansing helps prevent errors like making inaccurate pricing decisions, sending duplicate emails to clients, or spending resources on ineffective data analysis.
  • Enhanced Data Analysis: Clean data provides a firm foundation for data analysis, allowing professionals and company owners to conduct meaningful and trustworthy research. Data cleaning aids in the detection and correction of data-related problems that may interfere with analysis findings, ensuring that the insights acquired are valid and relevant.

The Most Efficient Data Cleansing Methods

Implementing improved data-cleansing procedures can aid in extracting usable information from datasets and removing numerous problems. There are several data cleansing methods available for quickly cleaning and improving data quality. Among the most regularly utilised approaches are:-

  • Standardisation method: This method of data cleansing constitutes the standardising of data to assure uniformity in units, format, and representations. This might include standardising dates, normalising addresses, or transforming data to a common measurement unit. Data standardisation can aid in the elimination of unreliable data, making it more comparable and accessible for analysis.
  • Data imputation: Filling up missing data with appropriate values based on statistical methods or domain expertise is known as data imputation. This can include approaches like mean, median, or mode imputation, as well as applying machine learning algorithms to estimate missing values based on data trends. Data imputation ensures that data is full and can be analysed without gaps.
  • Deduplication method: This method constitutes locating and deleting duplicate data records to minimise duplication and maintain data integrity. This might include finding and merging duplicate items based on specified rules, such as name, phone number, or address. Deduplication ensures that data is unique and prevents repetitive analysis and reporting.
  • Data verification: Data verification is another highly reliable data cleansing method that involves detecting and correcting discrepancies or inaccuracies in data by comparing it to trusted sources or reference data. It primarily involves cross-referencing data with other sources (databases, APIs, or reference data) to check their accuracy and dependability.
  • Automated data cleaning tools: Employing data cleaning tools or software that automates the data cleansing process is a fool-proof data cleansing method that makes the job a hundred times easier. These solutions may have built-in rules, algorithms, and validation tests that may be modified to rapidly and effectively clean and enhance data quality.
  • Data profiling: Profiling data to detect concerns in data quality, such as missing numbers, inaccurate values, or anomalies is another highly efficient data cleaning method. Data profiling approaches can give insights into data quality and assist in identifying areas that require cleaning or enhancement.

Conclusion

Data cleaning is one of the most effective ways to reduce inconsistencies that can lead to added costs. It is the most straightforward way to save expenses, minimise potential risks, as well as safeguard the company’s reputation. Finally, data cleaning is vital for guaranteeing the accuracy, consistency, and integrity of data, which is vital to making educated decisions, promoting corporate success, and ensuring compliance in various sectors. 

A career in data science and machine learning may be rewarding for people who enjoy working with data, solving complicated issues, and making a difference. But, before embarking on any job route, it is critical to conduct an extensive study and carefully assess your interests, talents, and career objectives. If you are passionate about pursuing this field, you can consider joining a data science and machine learning course offered by Imarticus Learning. 

Python: The Beginner’s Guide to Learning a Powerful Programming Language

Posted on by Imarticus Learning

Have you ever wanted to create your apps, games, websites, or software? Do you feel intimidated by the complexity of coding and the endless possibilities of technology? If so, you are not alone. Many people interested in programming feel overwhelmed by the information and skills they need to learn.

But don’t worry; there is a solution: Python. Anyone may learn Python, a straightforward, adaptable, and well-liked programming language. Python has been created to be simple to read, write, and comprehend. It offers a comprehensive library of modules and packages that may assist you with practically any work, straightforward and consistent syntax, and a wealth of built-in capabilities.

Data Science Course

This blog will demonstrate why Python is the ideal programming language for newcomers. By the end of this post, you’ll have a strong foundation in Python knowledge and a zeal for coding.

Why Python?

Python is one of the most widely used and loved programming languages worldwide. A high-level, all-purpose programming language is Python. Its design philosophy strongly emphasizes code readability through off-side rule-based considerable indentation.

Python has dynamic typing and uses garbage collection. It also supports programming paradigms, including object-oriented, procedural, functional, and structured programming. 

But what makes Python so special?

Here are some of the main reasons why Python programming for beginners is ideal :

  • Python is easy to learn. Python has a simple and expressive syntax that resembles natural language. It uses indentation to structure code blocks, which makes it more readable and elegant. Python also has fewer keywords and rules than other languages, which means less memorization and confusion.
  • Python is versatile. Python can be used for various applications, such as web development, data analysis, machine learning, artificial intelligence, automation, game development, and more. This means you can choose the best approach for your problem and learn different ways of thinking.
  • Python is powerful. Python has a rich set of built-in data types, functions, and operators that can easily handle complex operations. Python also has a huge collection of external modules and packages that extend its functionality and provide ready-made solutions for common problems. For example, you can use NumPy for numerical computing, Pandas for data manipulation, Matplotlib for data visualization, Django for web development, TensorFlow for machine learning, PyGame for game development, and many more.
  • Python is fun. Python is not only a practical tool but also a creative medium. You can use Python to express your ideas and imagination in code. You can create interactive games, animations, art, music, or anything else. You can also explore the fascinating world of computer science and discover new concepts and techniques that will challenge and inspire you.

Python Demand in the job market 2023

By 2023, there will be a tremendous need in the job market for those with Python knowledge. Python has become a popular programming language for various businesses and occupations. Its adaptability, simplicity, and breadth of uses have helped make it popular with employers worldwide.

How to learn Python as a beginner?

Python: A potent programming language for learners

Learning Python is a fantastic experience. It starts with a straightforward curiosity or inspiration. Python may have caught your attention because of its versatility and power. You want to learn more and explore your creative potential with this potent language.

You set off on your trip. You watch videos, read tutorials, and enroll in courses. Variables, data types, operators, and control flow are all things you learn. As you create straightforward applications, Python’s potential becomes apparent.

However, Python is more than simply a language, as you learn more about it. It’s a technique for handling issues and thinking. It’s a method for producing items that are both attractive and practical. Mastering Python basics from scratch is a challenging but rewarding journey.

Learning the basics of Python requires time and work, but it is ultimately worthwhile. You’ll be able to create Python programs that are effective and strong if you have a firm understanding of the fundamentals.

  • Start with the fundamentals. Avoid attempting to absorb everything at a time. Start with the basics, and add to your knowledge as you go.
  • Exercise often. Practice is the key to learning Python. Even if it’s only a simple application, make an effort to write some code every day.
  • Build initiatives. Building projects is one of the greatest methods to learn Python. This will enable you to put the ideas you’ve learned into practice and discover how they might be used in actual situations.
  • Never hesitate to seek assistance. Ask for help if you run into trouble. You may ask questions and receive assistance in several online groups and forums.
  • Have Fun! Python training should be enjoyable. You’re less inclined to persevere if you’re not having fun. You’ll succeed if you can discover ways to make studying Python entertaining.

Mastering the Essentials – Python Language Basics

  • Variables: Variables are used to store data. Any kind of data, including integers, strings, and lists, may be sent to them.
  • Operators: When working with data, operators are employed. Operators can be logical, comparison, or arithmetic operators.
  • Expressions: Variables, operators, and values make up expressions. They may be applied to decision-making and value calculations.
  • Control flow statements: Statements that govern the execution flow of a Python program are known as control flow statements. They consist of while loops, for loops, and if expressions.
  • Functions: Reusable code chunks are referred to as functions. The def keyword is used to define them.
  • Modules: Collections of variables and functions that may be imported into other Python programs are known as modules.

Participate in open-source initiatives. Participating in open-source projects is an excellent additional method of learning Python. This is a fantastic method to interact with the Python community and get knowledge from other programmers. You may contribute to various open-source initiatives, including Django, Flask, and NumPy.  

The Final Words

Python is a good programming language for beginners who want to learn how to code and create amazing things. Python is easy to understand, versatile, powerful, and fun. You can learn Python today by following simple steps and using helpful resources. You can join the Python community and connect with other learners and experts.

A joint initiative between Imarticus Learning and iHUB DivyaSampark at IIT Roorkee, the Certificate Program in Data Science and Machine Learning seeks to provide early and mid-career professionals with a solid foundation in a career in data science and machine learning. This extensive 5-month curriculum, created by prominent IIT professors, explores data mining, Python-based machine learning tools, and using data-driven insights to stimulate organizational growth.

Real-World Applications: How a Data Science Certificate Program Prepares You for the Industry?

Posted on by Imarticus Learning

Data science has emerged as a crucial field in today’s digital age. With the increasing reliance on data-driven decision-making, businesses across various industries constantly need skilled professionals who can harness the power of data to gain valuable insights. 

Data science is an interdisciplinary academic discipline that draws information and insights from noisy, structured, and unstructured data using statistics, scientific computing, and scientific techniques, procedures, algorithms, and systems.

This blog post will explore how a Data Science Certification Program readies you for the field. Whether you are a seasoned professional looking to upskill or a recent graduate considering a career in data science, this post will shed light on the real-world applications and benefits of a data science certificate program.

How a Data Science Certificate Program Enhances Employability in the Industry?

In the field of data science, there is a growing need for qualified personnel. Employing data scientists who can assist them in making sense of the enormous volumes of data they get is a top priority for businesses. But how can you distinguish yourself from the competition when many seek these desirable positions?

online Data Science certificate

Earning a certificate in data science is one option. You can acquire the abilities and information required for success in data science through a certificate program. You’ll gain knowledge of data collection, cleaning, and analysis techniques, as well as practical programming knowledge in Python and R.

The following are some extra advantages of completing a data science certificate program:

  • Gained expertise: A certificate program will provide you with a thorough introduction to data science, including subjects like statistics, machine learning, andthis post will shed light on the real-world applications and benefits of a data science certificate program. data visualization. Additionally, you’ll get practical experience working with actual projects and data sets.
  • Increased employability: Having a certificate in data science will help you stand out as a candidate for positions in this expanding industry. Employers are seeking employees with particular data science knowledge and abilities more frequently.
  • Professional development: Maintaining current with the most recent data science trends is possible with a certificate program. Along with learning about cutting-edge tools and methods, networking with other data scientists will be a chance for you.
  • Personal satisfaction: Learning about data science may be enlightening and satisfying academically. You’ll get a greater comprehension of how the world functions and be able to apply your abilities to change it for the better.

What are the Real-World Applications of a Data Science Certification?

  • Understanding the Fundamentals of Data Science

Before delving into the practical applications of data science, it is essential to grasp the fundamental concepts and techniques. A reputable data science certificate program provides a comprehensive understanding of statistics, programming languages such as Python and R, data manipulation, and data visualization. 

  • Exploring Predictive Analytics

One of the key applications of data science is predictive analytics. Data scientists can make informed predictions and forecasts by leveraging historical data and statistical modeling techniques. A data science certificate program teaches you to apply predictive analytics in real-world scenarios. From predicting customer behavior and market trends to forecasting sales and optimizing supply chain management, making accurate predictions empowers businesses to make data-driven decisions that drive growth and success.

  • Unveiling the Power of Machine Learning

Machine learning is revolutionizing industries across the board. From healthcare and finance to marketing and e-commerce, machine learning algorithms are employed to automate processes, identify patterns, and extract valuable insights from vast data. A data science certificate program equips you with the necessary skills and knowledge to develop and implement machine learning models. This empowers you to create intelligent systems that can automate tasks, improve efficiency, and enhance decision-making processes.

  • Harnessing the Potential of Natural Language Processing

Natural language processing (NLP) has become a vital data science component as technology advances. NLP enables computers to understand and interpret human language, enabling applications like sentiment analysis, chatbots, and language translation. A data science certificate program familiarizes you with the principles of NLP and provides hands-on experience in applying NLP techniques to solve real-world problems. By mastering NLP, you can contribute to developing innovative solutions that enhance communication and user experience.

  • Navigating Big Data Challenges

The explosion of data in recent years has presented both opportunities and challenges. Organizations are grappling with efficiently storing, processing, and analyzing massive datasets. A data science certificate program equips you with the tools and techniques to handle big data effectively. From distributed computing frameworks like Apache, Hadoop, and Spark to data querying languages like SQL and NoSQL, you acquire the skills to tackle big data challenges and extract valuable insights from complex datasets.

The Final Words

A data science certification program offers many real-world applications and prepares you for a successful career in the industry. By understanding the fundamentals of data science, exploring predictive analytics, harnessing the power of machine learning, leveraging natural language processing, and navigating significant data challenges, you become equipped with the skills and knowledge needed to excel in the data-driven world. 

The Certificate Program in Data Science and Machine Learning from Imarticus Learning is here to help you start your journey into the world of data science and machine learning. This thorough curriculum, created with iHUB DivyaSampark @IIT Roorkee, presents the core ideas and subtleties of data science and machine learning, giving you the skills to use these ideas in practical settings. 

In this 5-month curriculum, carefully crafted by renowned IIT faculty members, you will delve into the worlds of data mining and machine learning technologies using Python and explore how to use data-driven insights to create major organizational success.

 So, take the first step towards a rewarding career in data science by enrolling in a reputable data science certificate program today!

Leading Skills for Data Science Experts

Posted on by Imarticus Learning

In today’s age of technological innovation and digitisation, data is undoubtedly one of the most important resources for an organisation. It is one of the most crucial prerequisites for decision-making. Reports estimate that as much as 328.77 terabytes of data are generated on a daily basis. This has, in turn, led to an exponential growth in the demand for data scientists who can actually analyse the vast amount of data and use it for business purposes. 

Data Science Course

Some of the many industries that have caused such a high data scientist job demand include retail businesses, banks, healthcare providers, and insurance companies, among others. In order to succeed in this field, you need to have more than just a basic familiarity with code. 

This brings us to the question, what are the most important skills required to become a data science expert?

Let’s find out!

What is A Data Scientist?

Before delving into the details of the leading skills for data scientist experts, let’s first understand what is a data scientist and their roles and responsibilities. 

Simply put, a data scientist is a professional whose primary goal is to solve complex problems and make crucial data-driven decisions. They are responsible for analysing large and complex data sets in order to identify patterns, understand trends, and find any correlations that can help organisations gain valuable insights. 

The responsibilities of a data scientist may vary based on the organisation or the type of business they work for. Nonetheless, listed below are some of the most basic and common responsibilities that every data scientist is expected to fulfil.

  • Collaborating with different departments, such as product management, to understand the needs of the organisation and devise plans accordingly, 
  • Staying up-to-date with the latest technological trends and advancements
  • Applying statistical analysis methods and machine learning algorithms to derive insights from data
  • Identifying and engineering relevant features from data to enhance both the accuracy and effectiveness of models
  • Evaluating the performance of models using various metrics and validation techniques
  • Effectively communicating any valuable insights to stakeholders and non-technical audiences.
  • Exploring and visualising data via multiple statistical techniques and visualisation tools

Skills Required To Be A Data Scientist

The skills required to be a data science expert can broadly be divided into two types. They are, namely,

  • Technical skills and 
  • Non-technical skills

Technical Skills

Mentioned below are a few technical skills that every data science expert must possess

Programming: In order to excel in this field, you must have an in-depth knowledge of the crucial programming languages and not just Python. Such include C/C++, SQL, Java, and Perl. This will help you to organise unstructured data sets in an efficient manner.

Knowledge of Analytical Tools: Having a thorough understanding of the various analytical tools and how each of them operates is also a must for a data science expert. Some of the most commonly used tools include SAS, Spark, Hive and R, among others. 

Data Visualization: Data visualisation skills are important for communicating insights effectively. This includes proficiency in various visualisation libraries and tools such as Power BI and Tableau. All these facilitate the creation of interactive and visually appealing visualisations.

Data Mining and Text Mining: A deep understanding of various data mining techniques, such as clustering, or association rules, can also prove to be extremely useful, especially for uncovering hidden patterns and relationships in data. Additionally, you are also required to possess text mining skills such as natural language processing and sentiment analysis to be able to extract valuable insights from unstructured text data.

Non-Technical Skills

Non-technical skills also referred to as soft skills, are as crucial as technical skills. Therefore, they should never be ignored. Here are some of the most important non-technical skills you must possess in order to be successful in this field.

Communication: The nature of this field is such that it requires you to communicate with various departments and individuals on a daily basis. Therefore you must possess excellent communication skills so that you can communicate your ideas and thoughts to different team members in an efficient and precise manner. 

Strong Business Acumen: Understanding the business context and organisation goals is crucial for every data science expert. You must be able to align all the data science initiatives with business objectives while simultaneously providing actionable insights that will add some sort of value to the overall business. 

Analytical Thinking: Other than these, a data science expert must also possess strong analytical thinking abilities. In this manner, you can approach any given problem in a logical and structured manner. You must be able to break down any large and complex issue into smaller and simpler subsets, analyse them individually, and design innovative solutions for the same.

 Adaptability: The field of data science is continuously evolving, with innovations and advancements happening every day. Therefore, as a data science expert, you must possess the ability to embrace these new changes and stay up to date with the latest innovations in technologies, methodologies or approaches. In this manner, you will always remain one step ahead of your competitors and eventually gain success.

Conclusion

While all these technical and non-technical skills are crucial for being successful as a data science expert, you are also required to have a strong educational background. This includes a Master’s degree or a PhD in computer science, engineering, statistics, or any other related field. Additionally, you can also opt for specialised courses that are designed to train students who wish to pursue a career in data science. 

One such includes the Post Graduate Program in Data Science and Analytics offered by Imarticus Learning. It is specifically designed for fresh graduates and professionals who wish to develop a successful data science career. With the help of this course, you can gain access to real-world applications of data science and explore various opportunities to build analytical models that enhance business outcomes. Additionally, you also get to enjoy several other benefits, such as career mentorship, interview preparation workshops, and one-on-one career counselling sessions, among others. 

Is a postgraduate program in data science worth the hype?

Posted on by Imarticus Learning

There is no doubt that data science is one of the most popular and in-demand fields today. 

And with the ever-growing amount of data being generated daily, the demand for qualified data scientists will only continue to increase.

A postgraduate program in data science can be an excellent investment for your future. The field of data science is constantly evolving, and having the latest skills and techniques can help you find more attractive job opportunities. And with the internet age, you can learn data science online right from home.

So, if you’re considering a data scientist career, a postgraduate program in data science is definitely worth the hype! 

In this blog, we’ll look at a few reasons why that’s the case

  • In-Demand Field

Data science is one of the most in-demand fields today. Companies are always looking for ways to improve their business operations and make better decisions. 

With the rapid growth of data-driven industries, there is a constant need for experts who can analyze and interpret large data sets.

Data science combines computer science, statistics, and mathematics skills to extract knowledge and insights from data using various techniques. They then use their findings to build predictive models and make business recommendations.

Data scientists use their skills to solve real-world marketing, finance, healthcare, and more problems.

  • Competitive Salary

A postgraduate program in data science can provide you with a competitive salary. With the right skills and experience, you can easily earn well enough.

In general, data science is a very lucrative career choice. The average industry salary for data analytics and machine learning roles is between Rs 5-25 Lacs. With the right skills and experience, you can easily earn well enough to support yourself and your family.

  • Make You Skilled

A postgraduate program in data science can help you build a successful career by equipping you with the latest tools and techniques to tackle real-world problems effectively.

The program will enable you to identify and solve complex business problems by applying data-driven methods. You will also learn to communicate your findings to decision-makers effectively.

Working on real-world projects will allow you to gain practical experience that will be invaluable in your future career. In addition to the practical experience, you will also gain a deep understanding of data science concepts. This will help you develop new skills and knowledge to apply to your future career.

  • Specialisation

A postgraduate program in data science will allow you to specialise in a particular area of data science. It will make you more valuable to potential employers, as you’ll be able to offer them a more specific skill set.

Many types of data science programs are available, so choosing one right for you is essential. Consider your career goals and the kind of data you want to work with before deciding.

You can become a data scientist, machine learning engineer, business analyst, AI engineer, web and social media analyst, ML consultant, etc. There are many possibilities for you to explore.

  • Networking

Networking is an important part of succeeding in any field, and data science is no exception. With the right approach, you can easily make connections that can help you advance your career.

In addition to networking, postgraduate programs in data science can also help you learn from some of the best minds in the field. You’ll have access to lectures and seminars from world-renowned data scientists, and you’ll be able to learn from their experiences. This can help you develop the skills you need to succeed in your career.

  • Certification

The certification from a prestigious institute will put a stamp of authority beside your name and give you credibility. Your employers will feel more confident in working with you.

Conclusion

Data science is a rapidly growing field, and there will be plenty of opportunities for you to advance your career. With the right skills and experience, you can easily become a leader in the field.

You can learn data science online if you’re looking to pursue a data scientist career. Imarticus Learning offers a data science course with placement. It’s designed for students who want to learn data science from the ground up, and it includes complete access to our online learning platform, so you can start putting your skills to use immediately. You can visit one of their centers to learn more about the program.

If you’re considering a postgraduate program in data science, hesitate no more! The time to take the next step is now. 

Read This Quick Guide Before You Go For A Data Science Interview 

Posted on by Imarticus Learning

Read This Quick Guide Before You Go For A Data Science Interview 

First of all, congratulations on receiving an interview invitation for your dream job!

This article covers all the important information you need to prepare for your upcoming interview. But first, let’s look at the meaning and importance of data science. 

“Data is information, and data will define the future,” Prime Minister, Narendra Modi, remarked at the Audit Diwas event. This demonstrates the possibilities of data science and machine learning. Today, every business needs people who can translate cutting-edge technology into usable data insights. 

As a result, there is a greater demand for experienced data scientists to assist companies in making various decisions. This is an excellent opportunity to join this burgeoning sector. So, study data science, apply for your dream job, prepare for the interview, and get started as a data scientist.

Roles in Data Science

It’s critical to figure out which role is best for you:

  • Data Analyst: The most popular choice for persons who learn data science is a data analyst. Pulling data from SQL databases, performing exploratory data analysis, managing Google Analytics, assessing A/B test results, and understanding excel are all common jobs for data analysts.
  • Data Engineer: Individuals who specialize in creating and developing data infrastructures for data-driven businesses with a high volume of traffic are called data engineers. Designing data models, implementing data processing systems, and administering SQL and NoSQL databases are examples of everyday tasks.
  • Data Scientist: A data scientist’s job profile combines the responsibilities, tasks, and activities of both a data analyst and a data engineer. 

Data Science Interview Guide

  • Programming: Good programming abilities are mentioned in every job description as an eligibility requirement because no data science position is complete without the ability to alter data. Almost every technical interview begins with a programming question.
  • SQL skills: Every analyst is expected to be able to extract data from a relational or non-relational database. Several analyst job descriptions expressly call for experience developing complicated SQL queries to collect data. To crunch datasets, one should be familiar with Python libraries such as NumPy, pandas, and scipy.
  • Machine learning: Machine learning is a crucial topic to cover for data science jobs at the middle and senior levels. Algorithms, linear regression, machine learning problems, decision trees, and other topics should be covered.

Common Interview Questions

Preparing frequently asked data science interview questions is the best way to answer difficult questions and get your dream data science job. Following are a few commonly asked questions that you can prepare for:

  • Why do you want to enter the data science field?
  • What are the various ways to extract valuable insights from databases?
  • What are all the steps to make a decision tree?
  • How to use recommender systems in data science?
  • What all data science courses have you completed?

One of the best ways to learn and start a career as a data scientist is to complete the best data science courses.

Post Graduate Program (PGP) in Data Analytics and Machine Learning

The PGP in Data Analytics and Machine Learning is a nine-month part-time weekend-based working professional program. A six-month full-time program offered on weekdays is another option for completing the course. This program teaches you to apply data science in the real world and construct predictive models that improve business outcomes. 

This guaranteed job assurance program is excellent for recent graduates and professionals interested in pursuing a career as a data scientist. The PGP in Data Analytics and Machine Learning programs has the following benefits:

  • The data science course offers an assured placement program where students get interview calls and placement opportunities from top data science companies.
  • It follows an industry-oriented curriculum that companies around the world accept.
  • It is a perfect blend of practical and theoretical knowledge, where hands-on training is provided to students through various platforms and real-world case studies.

Conclusion

Data science is an ever-growing industry with ample job opportunities for fresh graduates and working professionals. Suppose you want to enter this field, pursue a data scientist career, complete various data science courses, and prepare well for the interview. The PGP in Data Analytics and Machine Learning can help you learn essential skills and topics related to data analytics, machine learning, and data science. So, join the course and delve into the world of data.

Contact us now, or visit one of our training centers in Mumbai, Thane, Pune, Bengaluru, Delhi, Chennai or Gurgaon for queries related to the PGP in Data Analytics and Machine Learning.

Related Articles:

The Perfect Guide To Understanding The Data Science Career Path
Transitioning to Data Science: How To Get There?
The Rise of Data Science in India: Jobs, Salary & Career Paths in 2022
Top 5 Trending Jobs In The Data Science Industry

Stop If You’re Looking For A Job-interview Guarantee Data Science Program

Posted on by Imarticus Learning

Introduction

Data is one of the most critical assets in the business world. Every company makes its market and future decisions based on data.

The importance of data and its widespread applications has led to a sharp increase in the demand for professionals who have studied data science. These experts can quickly analyse the data and convert it into meaningful business numbers.

No wonder data science is one of the most sought-after professional courses. Companies are willing to offer high salary packages to individuals with data science training.

A data science course with  job interview is your key to unlocking a flourishing career with endless opportunities

Problems with Available Data Science Programs

Most data science online training programs do not come with guaranteed job interviews. Another problem is the lack of practical sessions for the students to gain hands-on knowledge.

Online availability of learning resources is one of the main requirements, allowing students the flexibility to learn remotely.

Your data science online training module must include a good mix of theory-based and practical training. After all, such courses are meant to leave you future-ready. However, many data science courses are found to lack all these offerings.

What Should You Look Out For?

Selecting a course that provides job interview guarantee in a reputed company is one of the best ways to put your career on the right track.

leadership training programs

If you enrol for a data science course, mere theoretical understanding will not suffice. You need practical knowledge too.

Professional Data science online training and courses will equip you with the following skills:

  • Probability and Statistics
  • Multivariate Calculus and Linear Algebra
  • Programming, Packages, and Software
  • Data Wrangling
  • Database Management
  • Data Visualisation
  • Machine Learning
  • Deep Learning
  • Cloud Computing

What are the Top 10 Reasons to Learn Data Science Course in 2022?

With the rapid digitizations of systems worldwide, data-driven decision-making is gaining momentum. Hence, a profession in data science has become the rage.

Most companies look for talented and proficient employees, no matter how small or large. They seek people who can research the data precisely, thus making it the most alluring job and hot career in any domain.

Here, we have assembled the top 8 benefits data science certification offers in 2022.

  • High Salary.
  • Job Opportunities.
  • Offers Quick Growth.
  • Add Value to the Business.
  • Future Focused Career.
  • Center of Decision Making.
  • Freelancing Opportunities.

How to Select A Data Science Program?

Consider a data science course with job interview, where the central focus is on using data science to build predictive models and real-life applications. It should help you grasp the basic principles of data analytics and machine learning – tools in demand in the market.

The course should, additionally, give you a good enough practical knowledge of Python, SQL, Data Analytics, and more. The course content should always be available for review and learning online, always. It would help to revise the content from any place, anytime. Also, ensure that the data science online training program you choose covers all the necessary topics.

You want to pursue a career in data science but are unsure where to start. The world of deep tech is continually changing, so it’s crucial to stay ahead of the curve by continuing your education. Here are a few factors that will help you choose the perfect course.

  • Define your goals.
  • Do your research.
  • Consider your learning style.
  • Check the credentials of the instructors.
  • Look at the reviews.
  • Make sure the course is updated.
  • Determine the value for money.

Final Thoughts

If you’re looking for an ideal data science online training program, the Imarticus learning program will prove right for you because:

  • The course format is easy to follow.
  • We have more than 300 companies and over 35,000 learners enrolled with us.
  • We provide you with quality career support.
  • Experienced and expert creators and tutors have created each course.
  • We aim to enrich students’ careers by helping them learn new skills.
  • Our fee structure is quite reasonable.

Connect with us through chat support on our Contact Us page. Alternatively, you can visit our training centers located in cities like Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, and Ahmedabad.

Transitioning to Data Science: How To Get There?

Posted on by Imarticus Learning

Transitioning to Data Science: How To Get There?

The emergence of big data has prompted businesses to rely on data to make informed decisions. But how do you make sense of all that data?  That’s where the data scientist enters the scene.

A data scientist collects, analyses, and interprets data to make business recommendations. They do this by using AI, Statistics, and Computer science. They can apply these skills to a wide range of industries such as healthcare, finance, and retail.

The Data science career is an excellent choice for those interested in working with data. And it’s pretty rewarding with the right skills. Whether you want to advance in your career in data science or start, many options are available. One of the most effective ways is through data science courses.

These courses enable students with the right skills and knowledge to succeed. Let’s explore how you can transition with the help of proper data science online training.

Transitioning to Data Science via Applied Learning Courses 

The easiest way to transition to the data science space is to learn the fundamentals of the subject. Consider enrolling in a data science online training program that incorporates applied learning.

This learning method is convenient since students are not restricted to physical classrooms. Also, it offers students the flexibility to learn at their own pace, anywhere, and at any time. 

The learning model in an online environment is flexible and includes various resources. These include videos, lectures, articles, books, and one-on-one interactions with the instructor. Next, let’s talk about what you’ll need to learn in your data science course.

Data Science Online Training Curriculum

To transition into data science, you’ll need to learn the fundamental concepts, including:

  • Statistics
  • Probability Theory
  • Probability Distributions
  • Hypothesis Testing
  • Statistical Tests

These topics form the core of any data science course. Moreover, an understanding of Machine learning and Predictive Modelling is also required. Apart from these topics, you’ll also learn about some essential tools and languages. These include:

  • Python
  • Tableau
  • SQL
  • NumPy
  • Pandas

Combining these tools with fundamental concepts will help you in your data role.

What Makes a Good Data Science Online Training?

So, we’ve considered the curriculum requisites for transitioning into a data science career. Now, let’s examine what makes a great data science course based on applied learning: Faculty from top institutes such as IIT/IIM and other industry experts.

  • Live instructor-led online sessions with access to the session recordings and notes.
  • Online discussion with course faculty and peers to clear doubts and brainstorm.
  • Real-world case studies and live projects to provide insight. These concepts can predict property value, heart disease, taxi fare, etc.
  • Regular assignment assessments to track progress.
  • A Capstone project to collate and present the course learnings.
  • Career support activities, including resume-building workshops and mock interviews for job placements.
  • Startup mentorship and funding for those looking to start their ventures.
  • Certification of completion.
  • Access to an alumni network and a chance for an on-campus immersion program.

A course providing these things will ensure that you learn data science skills and make data-driven decisions. One such data science online training based on the concept of applied learning is offered by Imaticus Learning.

About Imaticus Learning

Imarticus Learning, in collaboration with iHUB DivyaSampark @ IIT Roorkee and the Department of Science & Technology (DST), offers one of the best certification programs in Data Science and Machine Learning. 

Since the program is made especially for the early and mid-level professionals, you’ll understand the various aspects of data science and learn how to implement and apply these concepts to real-world problems. 

Imaticus Learning covers all the points that make for excellent data science online training program, as mentioned earlier. Check out the success stories of those who transitioned into the data science field. Some alumni work with big brands such as Accenture, Capgemini, KPMG, etc.

You can visit the Imarticus Learning website for live chat support. You can also drive to one of their training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Conclusion

As data becomes central to decision-making in organizations, those with the skills to analyze and interpret it will be in high demand. Starting or transitioning to a data science career requires a strong foundation. And to help you with that, you can look for result-oriented data science courses.

Attending these courses helps you develop the skills needed to become a top Data scientist, Data Analyst, Business analyst, Data manager, Business Intelligence expert, etc.

This blog discussed what constitutes a top data science online training program and explored one such institute in Imaticus Learning. Feel free to check it out. Also, let us know your opinion on the necessary things for transitioning into the data science career.

Techtrek In 2022: Here’s How Data Scientists Successfully Adopt The Data-Driven Culture

Posted on by Imarticus Learning

Techtrek In 2022: Here’s How Data Scientists Successfully Adopt The Data-Driven Culture

Given the enormous volumes of data created today, data science is an essential factor in many sectors and is one of the most debated issues in IT. Since data science has become increasingly popular, businesses have begun to use it to expand their operations and improve consumer happiness. 

The field of study known as data science works with enormous amounts of data using cutting-edge tools and methods to uncover hidden patterns, glean valuable information, and make business choices. Data science creates prediction models using sophisticated machine learning techniques. This post will explain how data scientists successfully adapt to the data-driven culture.

The Benefits of a Data-Driven Culture

Having a data-driven culture that propels the company forward has several benefits. 

Organizations are encouraged to use reliable data when making choices by a data-driven culture. For any organization, interpreting data and exercising critical thinking are essential. However, a data-driven culture aids businesses in determining when to and when not to make decisions based on data.

It is accomplished by continuously monitoring performance and plays a significant part in continuous improvement inside the organization. Additionally, it aids in the advancement of analytically-based business choices. Organizations may move away from utilizing data only to generate reports and measure their development with the aid of a data-driven culture. 

The Challenges of Implementing A Data-Driven Culture

Despite the increased investment, many businesses find it challenging to keep their data strategy moving forward. According to a recent report, 72% of significant companies have failed to establish a data-driven culture.

Although many organizations invest more and more resources in their data strategy, successful plan execution gets frequently hampered by large organizations’ sheer size and complexity.

It’s crucial to ensure that data and analytics are available in a tangible, intelligible manner and can immediately connect with the operations they perform and their choices to improve analytics adoption.

Teams that want to succeed should frequently allow end-users some liberty by putting the proper technologies in place to provide self-service analytics that considers local complexity.

Future developments in IoT, AI, big data analytics, blockchain, and quantum computing will be incredibly significant.

Explore a data science career with Imarticus Learning

Students may start in data science and machine learning with this certificate program. Students will master the fundamentals of data science and machine learning through this curriculum, developed in partnership with iHUB DivyaSampark @IIT Roorkee, and acquire the knowledge and abilities they need to apply these concepts to problems in the real world.

Course Benefits For Learners:

  • This five-month program, developed by renowned IIT faculty members, will instruct students in using Python to comprehend data mining and machine learning methodologies.
  • The data science certification course will be live via online sessions with India’s best educators.
  • With the help of this data science online training, students will be able to develop a solid foundation in data science.

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

The Perfect Guide To Understanding The Data Science Career Path

Posted on by Imarticus Learning

The Perfect Guide To Understanding The Data Science Career Path

India is rising and shining brightly when it comes to adopting new and emerging technology. Almost every significant industry segment recruits data science specialists to help them gain meaningful insights from massive data. The analytics sector has seen considerable demand for highly qualified employees who understand business and technology. Organizations nowadays are always on the hunt for specialists who can cover this ever-growing talent gap.

What is data science?

To develop insights from data, data scientists mix probability, statistics, and machine learning with domain expertise. These insights range from forecasting outcomes and trends to displaying linkages and patterns.

Data science impacts practically everything we encounter, from tailored playlists to shopping recommendations to illness diagnoses. Data scientists are also pioneers in developing self-driving vehicles, chatbots, and our data-driven environment.

A Career Path of Data Science Professional

Many data scientists have difficulty locating data science profiles and determining whether their skills match the job description. Because this is a relatively new industry, most organizations are imaginative regarding titles and career routes. This is also since these titles have no apparent precedent. Data science careers are expanding rapidly, with numerous vacancies across all industries. 

How do you begin a career in data science?

    1. Get educated – A good data scientist must have a solid math and statistics foundation. Getting extra education is essential if you’re not strong in these areas.
    2. Start playing with data – Use publicly available data sets to practice your data wrangling, analysis, and visualization skills.
    3. Get involved in the community – The data science community is vibrant and supportive. There are many online forums where you can ask questions and get advice from experienced data scientists. Community involvement will help you learn and grow in your career.
    4. Find a mentor – A mentor can be a great asset in your data science journey. Find someone experienced in the field who can help guide you as you learn and grow in your career.
    5. Keep learning – As a data scientist, you must continuously learn new techniques and tools. Many excellent resources are available, such as online courses, books, and blog posts.

Explore a data science career with Imarticus Learning

Students may start in data science and machine learning with this certificate program. Students will master the fundamentals of data science and machine learning through this curriculum, developed in partnership with iHUB DivyaSampark @IIT Roorkee, and acquire the knowledge and abilities they need to apply these concepts to problems in the real world.

Course Benefits For Learners:

  • This five-month program, developed by renowned IIT faculty members, will instruct students in using Python to comprehend data mining and machine learning methodologies.
  • The data science course will be live via online sessions with India’s best educators.
  • With the help of this data science online training, students will be able to develop a solid foundation in data science.