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Meta's AI Research Head Joelle Pineau Resigns After Eight Years

Meta’s AI Research Head Joelle Pineau Resigns After Eight Years

Meta’s vice president for AI research, Joelle Pineau, said she is leaving the company at the end of May after working 8 years for it.

Amidst the rapidly increasing competition in AI development, the head of AI research at Meta announced her departure from a high-profile position at the Instagram and Facebook company.

In her social media post, she wrote, “Today, as the world undergoes significant change, as the race for AI accelerates, and as Meta prepares for its next chapter, it is time to create space for others to pursue the work”.

Meta did not immediately respond to an emailed inquiry about Joelle Pineau’s decision to step down. Pineau herself has not yet announced who will take over her role.

Situated in Montreal, where Pineau also holds a professorship in computer science at McGill University, she was a key figure in Meta’s open-source AI strategy, notably with their Llama language model.

The announcement of Pineau’s departure comes before Meta’s inaugural LlamaCon AI conference on April 29th. Her leadership of Meta’s AI research began in 2023; this group, originally called Facebook AI Research, was founded ten years earlier by figures like the groundbreaking AI researcher Yann LeCun. Despite leaving his position as the group’s director in 2018, LeCun is still Meta’s chief AI scientist.

Source: https://www.business-standard.com/technology/tech-news/meta-s-ai-research-head-joelle-pineau-to-step-down-after-eight-years-125040200063_1.html

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A class 10 Student Made Over ₹1.5 lakh in 2 Months Building AI Websites, Claims Redditor

A class 10 Student Made Over ₹1.5 lakh in 2 Months Building AI Websites, Claims Redditor

Amid the job-loss fear arising from increasing implementation of AI (artificial intelligence), a Reddit post went viral about a Class 10 student in India, nicknamed “Musk” on the platform, making money with AI.

This kid used an AI website builder, spent just ₹2,500 and made over ₹1.5 lakh in two months by building and selling eight websites for around $250-$300 each.

According to the Reddit post, the founder of the AI platform, who spotted “Musk’s” success via user data, was impressed by the student’s hustle. “He was using our platform almost daily, buying credits, and building websites for small businesses. I got curious and checked his profile- turns out, he’s just a school student!”

What makes this story even interesting is that “Musk” isn’t a programmer. He’s just a creative and curious individual who saw AI not as a threat but as an opportunity to generate income by tapping into local and online networks.

The student was a regular user of Reddit who purchased credits and built websites frequently. By spending a nominal amount of ₹2,500 (approximately $30) on the AI-powered website builder platform, he earned more than ₹1.5 lakh within two months.

This student reached out to local businesses, social platforms, and Reddit communities proactively to find clients for his websites.

Source: https://www.businesstoday.in/latest/trends/story/india-isnt-for-beginners-redditor-claims-class-10-student-made-over-rs15-lakh-in-2-months-building-websites-using-ai-470001-2025-03-30

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Improve Web Design Skills

How To Improve Web Design Skills- A Complete Guide

How do you convert your passion for design into a rewarding career in this ferociously competitive digital landscape? The foundation for success is developing comprehensive web design skills, specifically in UI and UX. Learn actionable strategies to thrive in the ever-evolving world of web design and build a sustainable career. Let’s dive in!

Great user experience websites aid businesses in gaining new customers and retaining existing ones. As a poor mobile experience repels potential customers from a business (no matter how great its product/service is), many brands heavily invest in their UI/UX to avoid this scenario.

This investment translates into a booming job market in web designing. No matter how seasoned you are, honing your skills can boost your career and unlock bigger opportunities and a fatter paycheck.

Many professionals are actively refining their skills through courses, tutorials, blogs, and other resources. From 2017 to 2021, the enrolments in web development and website design courses increased by 230%.

Whether you are just starting out as a web designer or are experienced in UI UX designing, solidifying your skills will carve your way to becoming a distinguished web designer. 

This blog will not only guide you through essential strategies to elevate your web design skills but also reveal the transformative benefits that come from improving your craft.

Let’s get started!

Benefits of Enhancing Web Design Skills

Benefits of Enhancing Web Design Skills

“Have no fear of perfection—you’ll never reach it.” – Salvador Dalí. 

This famous quote by Salvador Dali indicates that improvement is an ongoing process. As a web designer, you should not let fear of not being perfect stop you from trying new things and stretching your limits. 

Investing your efforts and time into improving your web design skills offers plentiful personal and professional benefits. 

As best UI UX websites serve as revenue-generating machines for businesses, companies heavily invest in the look and feel of websites to offer the best experience to their users. 

From unlocking lucrative career opportunities to embarking on a lifelong learning journey, the web designing field offers deeply satisfying rewards. Enhancing web design skills offers a plethora of benefits in today’s digital-first world. Here is the breakdown:

Higher Earning Potential

When you keep improving your web design skills, you become a more specialised and refined developer. This increases your value in the job market, enhancing your earning potential. Many companies, including big firms and startups are ready to invest in designers who have the expertise in delivering exceptional results, specifically in web UI UX. 

In 2024, UI/UX designers in India with 1 or 2 years of experience had an average annual salary of ₹2,00,000. With 3 to 4 years of experience, this average doubles, and it’s possible to earn over ₹10,00,000 per year. Mastering in-demand skills enables you to command a high salary in the marketplace. 

In essence, if you develop skills to build highly functional and visually stunning websites, you can translate this potential into a big paycheck.

Increased Job Opportunities

In today’s digital-first age, from startups to giants, businesses are prioritising web designers who can create stunning user experiences for all their customers. When you enhance your web design skills with UI and UX principles, you gain expertise to create visually appealing, easy-to-use, and highly functional websites. 

When you keep polishing your craft, you position yourself as a valuable asset to potential employers and clients. This significantly enhances your chances of landing a high-paying job in the web design industry. These skills can be acquired through a practical-focused web design with UI/UX course.

Improved Career Advancement

In 2021, a LinkedIn study showed that UI and UX design were in the top 10 of the skills employers were actively looking for. As the demand for web designers with UI UX expertise is on the rise, enhancing your skills can give you a great career advancement.

Designers who can demonstrate a strong understanding of user-centred design principles are highly demanded in the market. Polishing your web design skills makes you highly sought after and a valuable asset for any organisation.

Expanded Technical Knowledge

Think of improving your web designing skills as powering up your craft. When you continuously learn, you go ahead of the basics and master advanced tools, techniques, and technologies. This significantly improves your technical knowledge.

The more technically sound you become, the more capable and versatile you will be as a web designer.

Diverse Career Paths

Website development skills are highly sought after in today’s digital-first world. Sharpening your web designing skills can open doors to a wide range of career opportunities. As a proficient web designer, you can explore various roles depending on your interest and skills, such as:

  • UI designer.
  • Web designer.
  • UX architect.
  • UI designer.
  • Front-end developer.
  • Web development lead.
  • Product Designer.

Improved Problem-Solving Skills

Web design involves working on complex projects. This job requires you to think critically and identify creative solutions. When you improve your web design skills, you strengthen your problem-solving abilities. This field not only solidifies your abilities in design but strengthens problem-solving skills in various other aspects. 

As a result, you learn to analyse problems, break down the issue into manageable steps, and build effective strategies to resolve them.

Enhanced Portfolio

Your web design portfolio is a representation of your expertise. It showcases your skills and ability to adapt to new trends and technologies. By improving your web design skills continuously, you can add more visually appealing, innovative, and complex projects to your portfolio.

A robust portfolio positions you as a valuable asset to your potential clients and employers. This leads to high-quality projects and more career opportunities. 

Ability to Adapt to Industry Changes

The web designing industry constantly evolves with new trends and technologies. This persuades a web designer to continuously learn and improve skills to walk hand-in-hand with evolving technology in order to stay relevant. 

This adaptability ensures long-term success as web designers who can embrace challenges and opportunities. On the other hand, professionals who are not polishing their web design skills are left behind.

Increased Efficiency and Productivity

Once you start refining your web design skills, you naturally become efficient and faster in your work. You will be abreast with the best techniques and tools, which will enable you to complete tasks quickly while maintaining quality.

You can efficiently handle projects even the most complex ones, meet the deadlines with ease, and be a more valuable asset for employers. 

Tips On Improving Web Design Skills

Tips On Improving Web Design Skills

Web design is a dynamic field that demands consistent learning and adaptation. If you want to flourish in your field, you need to keep improving your web design skills. Here is a list of tips that will help you grow as a web designer and polish your skills.

Master the Fundamentals

JavaScript, CSS, and HTML are core toolkit. Having a solid understanding of these languages enables you to structure the content effectively, add essential interactive elements, and style it precisely. 

Without a strong foundation in these toolkits, tackling intricate designs will be challenging for you. Therefore, invest your time in how these languages work together to build the robust backbone of any website.

Embrace UX and UI Principles

A website should not only look visually appealing but also work well for all users. Here, a solid understanding of UX (user experience) and UI (user interface) is necessary. While UX principles help in creating intuitive navigation, enjoyable interactions, and logical information flow, UI focus on visual appeal that reinforces a specific brand. 

Good user interface websites are crucial to providing the best user experience. Comprehending and applying UX and UI principles ensures your web design is delightful to use as well as works effectively.

Practice Consistently

Just like any other craft, consistent practice is the key to polishing your web design skills. Dedicate your time to work on different projects regularly; even small ones make a big difference in your skills. 

Keep experimenting with different layouts, apply new techniques that you have learned recently, and don’t be afraid if anything goes wrong. This is how you learn and grow in the web design field. The more you practice, the more proficient and natural you become.

Stay Updated with Trends & Tech

The digital landscape is evolving rapidly, and web design is no exception. New design trends, technologies, and best practices keep emerging constantly. Set aside a time to read quality blogs, explore tools and frameworks, collaborate and contribute to communities, and follow industry readers.

This all will help you stay abreast with the current trends and emerging technologies in the web designing field. Keeping yourself updated ensures that your skills remain relevant and enables you to apply the latest advancements in your projects.

Build a Strong Portfolio

As a web designer, you should have a strong portfolio to showcase your talent. Your visual resume highlights a wide range of your best projects. This is what your potential employers or clients would want to see to analyse your capabilities.

Consider including your best work that elaborates your approach in a project and the result you attained from it. A well-crafted and strong portfolio is a powerful tool to land high-paying jobs in the web design UI UX field.

Summing Up

For almost every business, the best user experience websites is the key to connecting with customers and generating revenue. A website’s UX and UI play a pivotal role in giving an enjoyable experience to users, which is crucial in an era where customer behaviour is evolving rapidly. This has intensified the demand for website designers with UI and UX skills. 

If you want to delve deeper into the web design principles to sharpen your skills, you can explore our web design course with UI and UX in Kolkata. Our E&ICT- IIT Guwahati certified program is designed for professionals to improve their web design skills. Even if you have just started, our practical-focussed curriculum can navigate you from basic to advanced concepts easily.

So, don’t wait up! 

Get in touch with us, and let’s discuss how we can transform your web design career in 6 months!

FAQs

What skills are needed for a web designer?

Understanding HTML, CSS, and UX/UI principles and responsive design are the most important skills for a web designer. These are the web designer’s required skills in today’s competitive job market.

Is web design a hard skill?

The answer depends on your skill set and ability to grasp the concepts. A website developer’s skills require specific technical expertise and the ability to apply design principles effectively. This skill can be easily learned and improved with dedicated practice.

How to improve web design skills?

Consistent practice is the key in web design. To polish your skills and explore new techniques, aim for practicing a few hours each week. Regular practice can make a big difference. 

Should I focus on front-end or back-end development as a web designer?

As a web designer, you should primarily focus on front-end development. However, understanding back-end concepts can give you an added advantage.

How can I stay updated with the latest web design trends?

You can follow web design blogs, actively participate in the communities, and attend online conferences to stay abreast with the latest styles, technology, and trends.

How important is a portfolio for a web designer?

A portfolio is essential for a web designer. A strong portfolio showcases your web design skills in various areas, so make sure you include your best pieces with variations. 

How can I improve my understanding of UX and UI design?

To enhance your UX and UI, you need to gain in-depth knowledge of what makes websites easy, intuitive, and enjoyable to use. Check the apps and websites you like, including those which you don’t. Figure out why they don’t work; based on your findings, make your design better.

What kind of projects should I include in my web design portfolio?

Consider showcasing a wide range of projects in your portfolio that demonstrate your skills in different areas, like landing pages, websites, etc.

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MeitY Received Over 187 Proposals for Developing Large Language Models Under the IndiaAI Mission

MeitY Received Over 187 Proposals for Developing Large Language Models Under the IndiaAI Mission

The Ministry of Electronics and Information Technology (MietY) disclosed that researchers, entrepreneurs, and startups have responded enthusiastically to the IndiaAI mission. It has received around 187 proposals focused on creating homegrown large language models (LLMs).

Abhishek Singh, additional secretary at MietY, revealed that 187 proposals were submitted following a Call for Proposals launched on January 30, 2025.

At the Nano Electronics Roadshow and Conference on Semiconductor Ecosystem, Singh said, “We had received 67 initial proposals by Feb 15, followed by an additional 120 proposals by March 15”.

Through a call for proposals, the IndiaAI initiative seeks to develop foundational AI (artificial intelligence) models, encompassing both LLMs and SLMs, within the country.

V. Narayanan, ISRO Chairman, who was a participant in the roadshow and conference, highlighted the importance of further indigenisation.

He said, “If you talk about a launch vehicle, 90% of it is indigenous and 10% is imported and out of that 10% imported items, 90% is electronics. You must have a roadmap to ensure that this drops to under 10%”.

The overwhelming response to the IndiaAI mission reflects the country’s ambition for leadership and self-reliance.

Source: https://www.thehindu.com/news/cities/bangalore/good-response-to-india-ai-mission-miety/article69382239.ece

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According to Bill Gates, AI Will Replace Most Jobs, Except These Three

According to Bill Gates, AI Will Replace Most Jobs, Except These Three

Since OpenAI introduced ChatGPT in 2022, AI has remarkably impacted our thinking and daily practices. Despite AI chatbots currently serving as helping hands in many workplaces, professionals are anxious about potential job losses across different fields.

Microsoft co-founder Bill Gates, who last month predicted that AI would take over most tasks, has now shared his perspective on future-proof careers amidst the increasing global integration of this cutting-edge technology.

While figures such as NVIDIA’s Jensen Huang and OpenAI’s Sam Altman anticipate coding jobs being quickly impacted by AI, Bill Gates believes humans will still have a key role in many sectors.

The 69-year-old Gates sees AI as a valuable tool for biologists in areas like diagnosis and DNA analysis, but it lacks the creative insight for discoveries, so it won’t replace them. He also stated that AI wouldn’t replace energy experts due to the intricate nature of this field.

As generative AI is progressing rapidly, several leaders repeatedly point out its huge impact on work, which will exceed human capabilities in some fields.

According to Gates, the future looks a bit relaxing for those in coding, energy, and biology. However, for the rest of the professionals, the rising AI integration across sectors indicates immediate upskilling and innovation. We can anticipate an era where AI will not be a helper but a competitor.

Source: https://indianexpress.com/article/technology/artificial-intelligence/bill-gates-ai-proof-future-jobs-coding-energy-expert-biologists-9907512/

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Indian Police Will Leverage AI Technology to Track Released Criminals

Indian Police Will Leverage AI Technology to Track Released Criminals

Indian police are using AI (artificial intelligence) and cutting-edge technology to track released criminals. Andhra Pradesh police in Vijaywada have already started leveraging AI for jail monitoring to prevent anti-social behaviour.

The police state that AI monitoring will serve as an early warning system. If any suspicious behaviour is detected, local teams will be alerted instantly, which will potentially prevent crime and boost public safety.

Earlier, the absence of such a sophisticated post-release tracking left a blind spot for law enforcement.

By combining advanced AI tools, CCTV surveillance, and human intelligence, new technologies now offer an easier and more effective way to maintain detailed records of released prisoners across Andhra Pradesh and other states.

SV Rajashekhar Babu, NTR District Commissioner of Police, stated that facial recognition cameras at key public transit hubs and public areas enable police to monitor criminal activity and interactions.

CP Babu said, “If a person with a history of robbery or other criminal offenses is released, they usually visit family and friends first before planning their next steps. If we detect them contacting known criminals or planning illegal activities, we alert the local police to summon them and their family for counseling”.

“The Jail Monitoring System helps in preventing crime and serves as a deterrent for habitual offenders. If a released criminal is found frequently visiting Vijayawada without a valid reason, the police issue strict warnings. If they have a legitimate reason, we do not interfere. However, if their visits raise suspicion, we take preventive measures”, he added.

Additionally, the Vijayawada police report that their AI system has prevented almost 200 known criminals from entering the city, leading to a reduction in crime and disturbances.

Source: https://www.cryptotimes.io/2025/03/25/indian-police-to-use-ai-monitoring-to-track-released-criminals/

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The Rising Need For Upskilling Is Fueling AI Growth in India's Edtech Sector

The Rising Need For Upskilling Is Fueling AI Growth in India’s Edtech Sector

The Indian Edtech sector is experiencing a momentous transformation driven by rising demand for upskilling and the increasing implementation of AI (artificial intelligence). An increasing number of learners, from experienced to students, want to explore this cutting-edge technology.

BrightCHAMPS, an edtech firm providing educational courses for K-12 students, found that 58% of students worldwide have already integrated AI into their studies. In addition, 36% use this technology for homework.

Ravi Bhushan, founder and CEO of BrightCHAMPS stated that AI is among the most-demanded courses in the market today.

He said, “We exclusively launched a Gen AI course for kids. In the US, every fourth student is inquiring and enroling in AI courses. India is not very far behind compared to the US. In fact, Indian parents are more curious than US parents”.

Just launched eight months ago, the Gen AI course has become one of BrightCHAMPS’ top three best-selling courses out of its seven flagship programs.

Edtech unicorn Emeritus now offers over 20 ML (machine learning) and AI courses, with AI certificates dominating its top-selling programs.

Bhushan Heda, chief operating officer of Emeritus said, “We saw a surge of almost three times in enrolments for AI courses in 2024 compared to 2023, with 75% of our enrolments coming from professionals with more than 10 years of experience, primarily in IT, engineering, and consulting”.

According to the 2025 Global Workplace Skills Study, 96% of professionals desire AI readiness.

Imarticus Learning, an edtech provider of professional courses, offers 20% of its programs in emerging technologies, including AI. Its Gen AI course, specifically for executives and learners interested in AI applications, is among the top five sellers, as stated by founder Nikhil Barshikar.

Source: https://www.business-standard.com/companies/start-ups/indian-edtech-sector-rides-the-ai-wave-as-upskilling-gains-momentum-125032300561_1.html

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Top 10 Data Science Programming Languages in 2025

Top 10 Data Science Programming Languages in 2025

Considering a career in data science but don’t know which data science programming language will be your winning hand in 2025? We are here to illuminate your path by revealing top data Science languages that will propel your career forward. Let’s dive in!

“Data is the new oil.” — Clive Humby.

Undoubtedly, data science is a booming field. In 2022, the BFSI (banking, financial services, and insurance) sector in India had more than 18,000 open positions for data scientists. This figure demonstrates the growing need for data expertise in the country. 

Fueled by the soaring demand for data-driven insights, employers are actively recruiting experts with proficiency in the most powerful tools like Python, R, SQL, etc.

However, the data science domain is shifting constantly and the job market is becoming increasingly competitive. Here, your toolkit defines your potential and builds your data science career.

In this blog, we have unveiled the top 10 data science programming languages you need to break into this prospering field and stay relevant in 2025 and the years to come.

Data Science Programming Languages: Definition and Importance

Data science languages refer to specific programming languages that data scientists use to perform a wide range of tasks, from data analysis, and manipulation to modelling and more. Several institutes are offering data science courses in Kolkata, you need to choose according to your career goals.

Data science programming languages are essential tools that enable data scientists to interact with the data sets and extract meaningful insights from them. 

The essential elements of data scientist languages are as follows:

Data Science Programming Languages 

(Common Examples)

 Purpose  Key Capabilities 
Python, R, SQL, Java, Scala, JavaScript, Swift, Java, etc. Enables data scientists to write instructions for computers to analyse, process, and visualise data. Data Manipulation: Clean, transform, and organise data. Handles numerous data formats including JSON, CSV, etc.
Streamlines the development of algorithms for AI (artificial intelligence) and ML (machine learning). Machine Learning: Developing and training machine learning algorithms and implementing deep learning models.
Automate data-related tasks to make workflows more efficient.  Statistical Analysis: Carrying statistical tests and calculations and building statistical models.
Data visualisation: Creating graphs, charts, and other visual representations of data.
Data interaction: Running queries and managing database.

 

What is the Role of Programming Languages in Data Science?

Full Stack Web Development

Data science programming languages are fundamental to data science productivity. They enable data scientists to efficiently store, manipulate, and analyse data. 

Machine learning, geospatial analysis, automation, and other data science domains require strong programming skills for tasks, ranging from data extraction to statistical analysis.

Specialised programming languages streamline this process which significantly boosts productivity. From initial data collection to final insights presentation; each requires a specialised set of coding proficiencies. The following points highlight the role of programming languages in data science.

  • Clarifying the Objective: In this stage, goals are defined. This is a pre-coding stage where no programming is required. Here, it is about focusing on the problems and selecting the right tools. 
  • Data Acquisition: Essential for data profiling. SQL and NoSQL enable data scientists to extract data from both traditional databases and web-based sources.
  • Data Cleaning: Raw data is messy. Python and R, along with tools like Trifacta are leveraged to clean and prepare the data.
  • Data Analysis: Python for data science is popular but R and MATLAB provide libraries for statistical analysis.
  • Data Visualisation: This is about presenting the findings in a visually appealing form. Here, Python libraries like Seaborn and Pandas are used to create informative charts and graphs.

Top 10 Data Science Programming Languages in 2025

When discussing the best data scientist programming languages, it is vital to understand the ‘top’ choice depends on the task and goals of the data science professional. 

However, some programming languages have consistently stood out in the crowd due to their powerful libraries, versatility, and robust community support. Here is a list of top data science languages in 2025 and beyond.

1. Python

Python for data science

Python is an interpreted, high-level programming language widely known for its versatility, readability, and extensive libraries. Python is among the most used programming languages for data science. There are many reasons to learn Python including the best languages for data scientists.

Key Features of Python:

  • Simple syntax, easy to understand and learn.
  • Extensive libraries (NumPy, Pandas, sci-kit-learn, TensorFlow, Matplotlib).
  • Versatile, widely used for automation, web development, and scripting.
  • Compatible across different platforms.
  • Active, large, and supportive community. 

Applications in Data Science:

  • Data cleaning and manipulation.
  • Machine learning and deep learning.
  • Statistical analysis and modelling.
  • Data visualisation.
  • Automation of data workflows.

Career Opportunities

  • Data scientist.
  • Machine learning engineer.
  • AI researcher.
  • Data analyst.
  • Software engineer.

2. R

R programming for data science

After Python, R is one of the most used programming languages for data science. It is a powerful and versatile tool for statistical computing and graphics. Data science and R programming are closely related as it is used for data visualisation and statistical modelling. 

Key Features of R:

  • Provides a wide range of statistical techniques including time-series analysis, linear and nonlinear modelling, classification, and clustering.
  • ggplot2 and dplyr are popular R packages for visualisation and data manipulation.
  • Creates high-quality graphs and charts.
  • Seamlessly integrates with other programming languages like Python, C++, and Java.
  • Large and active community. 

Applications in Data Science:

  • Learn R for data science to build insightful visualisations that easily communicate data patterns.
  • R is widely used for financial modelling and risk analysis.
  • Leveraged to perform complex statistical analysis like regression analysis and hypothesis testing.
  • R packages are used to extract valuable information from large sets of data.
  • R programming for data science is widely used for biological data analysis.

Career Opportunities:

  • Data scientist.
  • Data analyst.
  • Financial analyst.
  • Research scientist.
  • Statistician.

3. SQL

SQL for data science

SQL stands for structured query language. It is a domain-specific language used for creating, managing and manipulating relational databases. SQL is among the best languages for data science.

Key Features of SQL:

  • Used in all data-driven applications.
  • Essential for data warehousing.
  • Data extraction and manipulation.
  • Standardised language for database interaction.
  • Performs complex queries efficiently.

Applications in Data Science:

  • Data warehousing and ETL (Extract, Transform, Load) processes.
  • Data extraction and manipulation from databases.
  • Data profiling and exploration.
  • Building data pipelines.

Career Opportunities:

  • Data engineer.
  • SQL developer.
  • Database administrator.
  • Data analyst.
  • Business intelligence analyst.

4. Java

Java for data science

Java is another popular data science programming language used widely by data scientists. This programming language is versatile, object-oriented, and high-level that has been a cornerstone of software development for many years.

Key Features of Java:

  • Java bytecode can run seamlessly across devices with a JVM (Java virtual machine).
  • Enables modular design, code reuse, and easy maintenance.
  • Robust memory management (garbage collection) and exception handling.
  • Offers a vast library of pre-built classes and functions.
  • Very large and active community.
  • Built-in security features, make it suitable for secure applications.

Applications in Data Science:

  • Java is used in frameworks like Apache Hadoop and Apache Spark for big data processing.
  • Ideal for building data pipelines that can handle large volumes of data.
  • Enables Java developers to work with machine learning tasks.
  • Java is used for data applications that need a high level of security and stability.

Career Opportunities

  • Big Data engineer.
  • Java developer.
  • Data engineer.
  • Software developer/engineer.
  • Quality Assurance (QA) Engineer.
  • Back-End Developer.

5. JavaScript

JavaScript for data science

JavaScript is the foundation of modern web development. This interpreted and high-level programming language is primarily used to add interactive and dynamic elements to web pages. This versatile language functions across client (browsers) and server (Node.js) environments.

Key Features of JavaScript:

  • Handles multiple tasks simultaneously which improves performance. 
  • Used for front-end and back-end development, mobile applications, and much more.
  • Responds quickly to user actions like keyword input, clicks, and mouse movements.
  • Client-side execution enables quick user feedback and a more responsive experience.
  • Dynamic typing offers flexible data manipulation.

Applications in Data Science:

  • Libraries help to create dynamic and interactive data visualisation for web-based reports and dashboards.
  • Used to create web applications that facilitate data analysis and display results.
  • Can be used to collect data from websites and APIs.
  • Allows running machine learning models directly in the browser.

Career Opportunities:

  • Full stack data scientist.
  • Data visualisation engineer.
  • Front-end data scientist.
  • JavaScript Engineer.
  • Full-Stack Developer.

6. Julia

Julia for data science

Julia is another popular programming language to learn for data science. It is a high-performance and high-level programming language specifically designed for computational science and numerical analysis. It offers the programmer-friendly experience of Python without sacrificing the high performance of C/Fortran.

Key Features of Julia:

  • Versatility, rapidity, and expressiveness make it ideal for a range of applications.
  • Multiple dispatch feature facilitates function behaviour to change based on the types of arguments passed.
  • Makes it easy for scientists and mathematicians to express complex mathematical operations.
  • Extensive libraries for various domains including data analysis, machine learning, visualisation, and scientific computing.

Applications in Data Science:

  • Develops and deploys high-performing machine learning models.
  • Provides ease of data analysis and statistical modelling.
  • Creates sophisticated financial models and simulations.
  • The high speed makes it useful for massive datasets.

Career Opportunities:

  • Data scientist.
  • Comutattional scientists.
  • Software developer.
  • Quantitative analyst.

7. Scala

Scala language for data science

Scala is a general-purpose programming language running on the JVM. It blends functional and object-oriented programming models. This programming language is scalable, concise, and expressive, making it suitable for a range of applications, from web development to big data processing. 

Key Features of Scala:

  • Supports all the core OOP (Object-Oriented Programming) principles like classes, objects, inheritance, and polymorphism.
  • Ideal for writing concise and predictable code.
  • Identifies errors at the compile stage. 
  • Provides powerful tools for multitasking which is essential for handling huge datasets and distributed systems. 
  • Efficiently handles large codebases and growing projects. 

Applications in Data Science:

  • Suitable for building high-performance data pipelines.
  • Provides tools for data preprocessing, model training, and prediction.
  • Ideal for building robust and efficient data engineering solutions.
  • Used for real-time data processing.

Career Opportunities:

  • Data engineer.
  • Big data developer.
  • Machine learning engineer.
  • Software developer.

8. C++

C++ for data science

C++ is one of the oldest and foundational programming languages. Developed in the early ’80s, this programming language is an extension of C that adds OOP capabilities.

Key Features of C++:

  • Supports classes, objects, inheritance, and polymorphism.
  • Its versatile function makes it ideal for a wide range of applications.
  • STL (Standard Template Library) offers a rich set of data structures and algorithms.
  • Maintains C’s efficiency when adding OOP features.

Applications in Data Science:

  • In real-time processing or high-frequency trading, it is used to optimise code.
  • Many data science libraries such as NumPy and TensorFlow, use C/C++ to run quickly.
  • Used to build software that gathers and processes data in real-time.

Career Opportunities

  • Data Science Infrastructure Engineer.
  • Game Developer.
  • Software Developer.
  • Systems Programmer.

9. Swift

Swift for data science

Swift is an intuitive and powerful programming language developed by Apple Inc. This programming language is fast, safe, and expressive which makes it ideal for a range of applications. It is increasingly used for data science and server-side development.

Key Features of Swift:

  • Prevent common programming errors as it emphasises safety.
  • High performance, often compared to compiled languages like C++.
  • Easy to read and write code due to clean and concise syntax.
  • Incorporates modern programming models.

Applications in Data Science:

  • Integrates machine learning workflows, enabling high-performance model development.
  • Suitable for numerical computing tasks which is vital for data science.
  • Developing libraries that enable data visualisation within Swift.
  • Developers can integrate machine learning models into their Swift applications.

Career Opportunities:

  • Machine learning engineer.
  • Data scientist.
  • Server-side developer.
  • iOS/macOS developer.

10. MATLAB

MATLAB for data science

MATLAB or Matrix Laboratory is a high-level programming language widely used by scientists and engineers for data analysis, numerical computation, simulation, and algorithm development. Developed by MathWorks, this programming language is ideal for mathematical computations. 

Key Features of MATLAB:

  • Handling matrices and arrays simplifies complex mathematical computations.
  • Offers a vast library of pre-built functions for various statistical, mathematical, and engineering tasks.
  • Provides powerful tools to create 2D and 3D plots, graphs, and visualisations.
  • Its interactive environment enables users to explore data, test algorithms, and visualise results in real time.

Applications in Data Science:

  • Used for data analysis and visualisation, identifying patterns, and extracting insights.
  • Provides tools for building and implementing machine learning algorithms.
  • Used for process and analysis of images and signals. 
  • Performs statistical analysis, regression analysis, and hypothesis testing.
  • Used for financial data analysis and building financial models.

Career Opportunities:

  • Data analyst.
  • Financial analyst.
  • Data scientist.
  • Control system engineers. 
  • Image and signal processing engineers.

Endnote

So, this was our handpicked list of top data science languages in 2025. While these programming languages build a strong foundation, the ‘best’ choice depends on your career goals, interests, and skills. 

With a growing demand for data scientists, investing in any of the above language proficiency can elevate your career. 

Whether you are embarking on a data science career journey or a seasoned professional, make sure you stay abreast with the latest developments in the field.

Remember!

 “The best way to learn data science is to do data science”–Chanin Nantasenamat 

So, don’t get left behind, start learning today.

Enrol in full stack data science course in Kolkata with AI & ML and become a highly sought-after expert who commands high salaries in a top-tiered tech company.

FAQs

What is the best programming language for beginners in data science?

Python for data science is widely recommended. Due to its simplicity, extensive libraries, and large community support, Python is easy to learn, and apply and is among the most used programming languages for data science. 

Should I learn Python or Java first?

For data science, Python is more preferred and widely used than Java. Due to ease of use and data-centric libraries, Python for data science is preferred whereas Java is leveraged for more general purposes. Python program is the best way to learn Python for data science.

How long does it take to become proficient in data science?

Acquiring proficiency in data science can take a few weeks to several months, depending on your coding skills, dedication, and practice.

Can a non-technical person become a data scientist?

Yes, with solid understanding and practical projects, even a non-technical person can learn data science programming and analytical skills. 

How long does it take to become proficient in a data science programming language?

A basic understanding of data science programming languages can be acquired in a few months. However, mastering data science programming languages requires consistent practice and hands-on experience.

Why is coding required in data science?

Yes, coding allows data analysis, manipulation, and automation. These tasks are crucial for extracting valuable insights and building models from data sets.

Which programming languages are essential for big data projects?

Python, Java, and Scala are widely used for big data projects. These along with R is one of the best programming languages for data science.

Can I transition to data science if I come from a non-technical background?

Yes, through dedicated learning and a practical-focussed full stack data science course with AI & ML, you can transit into this field. You need to build a strong foundation in statistics and programming for data science.  

Which programming language is ideal for data science: Python or R?

Although both programming languages are considered ideal, Python for data science is mostly favoured due to its broader applications and versatility. As far as data science R language is concerned, it excels in statistical analysis and visualisation.

How many programming languages should I learn for data science?

Python for data science is a great starting point. Additionally, learning R and SQL can enhance your capabilities.

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Government Officials Are in Discussions With Elon Musk's X Over Grok AI's Use of Offensive Language

Government Officials Are in Discussions With Elon Musk’s X Over Grok AI’s Use of Offensive Language

The Ministry of Electronics and Information Technology (MeitY) is in discussion with Elon Musk’s X regarding instances of Grok AI producing responses containing Hindi slang and foul language.

The IT ministry is examining the issue and taking steps to understand the reasons behind the chatbot’s inappropriate language.

Ministry sources are saying, “We are in touch, we are talking to them (X) to find out why it is happening and what are the issues. They are engaging with us”.

Grok AI recently surprised users with its use of slang and expletives when prompted, and delivered unexpectedly opinionated responses on topics like politics, movies, and celebrities.

Adding to the concern, the chatbot has employed regional slang and abusive terms in conversations. Surprisingly, it also described Elon Musk as a “major disinformation spreader”.

After a user on X used a Hindi expletive directed at Grok AI for a delayed response to a request, the AI replied with the same foul language. Furthermore, Grok is causing unease among Indian right-wing propagandists. 

Grok, created by xAI and launched in November 2023, is a powerful AI chatbot. Built on a sophisticated LLM (Large Language Model), it’s designed for natural conversation, reasoning, and problem-solving.

With ten times the power, Grok 3 was launched on February 17th with improved reasoning, fast searches, and handles text and images.

Source: https://www.business-standard.com/india-news/grok-ai-expletives-hindi-language-slangs-llm-meity-india-government-125032000146_1.html

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bill gates image on ai conference

India’s AI Leadership Will Drive Global Innovation, Says Bill Gates

New Delhi, 20 March 2025: Microsoft’s former CEO, Bill Gates highlighted India’s accomplishments in AI, expressing his belief that the nation’s leadership will propel global innovation.

While addressing the ‘Future Forward’ forum, a gathering of global leaders and changemakers, Gates said, “Similar to how DPI (Digital Public Infrastructure) has garnered global attention, India’s leadership in AI will drive innovation worldwide”.

Addressing an event, Gates revealed he spoke with Minister Ashwini Vaishnaw about India’s participation in the next AI Summit, with a focus on benefiting countries in the Global South

He said, “I recently spoke with the Minister of Electronics and Information Technology about the upcoming AI summit, which I believe will be a fantastic opportunity. The foundation will ensure that governments, especially from the Global South, participate and benefit from India’s advancements”.

Gates explained that AI will speed up progress in mRNA vaccines, agriculture, and malnutrition.

He said, “By gathering and analyzing data, we can make targeted interventions and eliminate the barriers that hold people back”

Bill Gates highlighted the strong capabilities of Indian companies in creating low-cost, high-quality vaccines, and acknowledged the strength of India’s healthcare sector.

Gates acknowledged the success of India’s vaccine production, emphasising the vital role of partnerships with Serum Institute, Bharat Biotech, and IRI in delivering affordable vaccines globally.

“Without Indian innovation, vaccines wouldn’t be as affordable or accessible”, he added.

Source:

https://cio.economictimes.indiatimes.com/news/artificial-intelligence/indias-leadership-in-ai-will-drive-innovation-worldwide-says-bill-gates/119201428

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