#Career in AI and ML

[ananyamehtablog]

PG Diploma in AI and ML: Shaping Future Business Leaders

[queenlua]

it's funny how, when i was in college, one of the reasons i decided not to go into academia

was because i did a semester of research with this computational linguistics research prof who i really liked

and the [redacted research project] went totally fine, but i couldn't shake the feeling of "ok tho, this seems to mostly consist of doing some funky transformations on the corpus of The Entire Internet, which is cool and all, but it doesn't feel like i'm... adding... much... to our understanding of the universe? doesn't this feel like Garbage In, Garbage Out to anyone else? sure, it's kinda neat that i can do some funky transformations on stuff i pulled from [basically-Reddit], but that's all it is?"

and then, years later, LLMs blow up and it's like. joke's on me buddy, do you know how much hype you can milk out of doing a couple funky transformations on stuff you pulled from Reddit

[khushidubeyblog]

PGDM Specialization in AI & ML: Preparing for the Future of Business and Technology

[ogxfuturetech]

The Comprehensive Guide to Web Development, Data Management, and More 

Introduction 

Everything today is technology driven in this digital world. There's a lot happening behind the scenes when you use your favorite apps, go to websites, and do other things with all of those zeroes and ones — or binary data. In this blog, I will be explaining what all these terminologies really means and other basics of web development, data management etc. We will be discussing them in the simplest way so that this becomes easy to understand for beginners or people who are even remotely interested about technology.  JOIN US

What is Web Development? 

Web development refers to the work and process of developing a website or web application that can run in a web browser. From laying out individual web page designs before we ever start coding, to how the layout will be implemented through HTML/CSS. There are two major fields of web development — front-end and back-end. 

Front-End Development 

Front-end development, also known as client-side development, is the part of web development that deals with what users see and interact with on their screens. It involves using languages like HTML, CSS, and JavaScript to create the visual elements of a website, such as buttons, forms, and images. JOIN US

HTML (HyperText Markup Language): 

HTML is the foundation of all website, it helps one to organize their content on web platform. It provides the default style to basic elements such as headings, paragraphs and links. 

CSS (Cascading Style Sheets):  

styles and formats HTML elements. It makes an attractive and user-friendly look of webpage as it controls the colors, fonts, layout. 

JavaScript :  

A language for adding interactivity to a website Users interact with items, like clicking a button to send in a form or viewing images within the slideshow. JOIN US

Back-End Development 

The difference while front-end development is all about what the user sees, back end involves everything that happens behind. The back-end consists of a server, database and application logic that runs on the web. 

Server: 

A server is a computer that holds website files and provides them to the user browser when they request it. Server-Side: These are populated by back-end developers who build and maintain servers using languages like Python, PHP or Ruby. 

Database:  

The place where a website keeps its data, from user details to content and settings The database is maintained with services like MySQL, PostgreSQL, or MongoDB. JOIN US

Application Logic —  

the code that links front-end and back-end It takes user input, gets data from the database and returns right informations to front-end area. 

Why Proper Data Management is Absolutely Critical 

Data management — Besides web development this is the most important a part of our Digital World. What Is Data Management? It includes practices, policies and procedures that are used to collect store secure data in controlled way. 

Data Storage –  

data after being collected needs to be stored securely such data can be stored in relational databases or cloud storage solutions. The most important aspect here is that the data should never be accessed by an unauthorized source or breached. JOIN US

Data processing:  

Right from storing the data, with Big Data you further move on to process it in order to make sense out of hordes of raw information. This includes cleansing the data (removing errors or redundancies), finding patterns among it, and producing ideas that could be useful for decision-making. 

Data Security:  

Another important part of data management is the security of it. It refers to defending data against unauthorized access, breaches or other potential vulnerabilities. You can do this with some basic security methods, mostly encryption and access controls as well as regular auditing of your systems. 

Other Critical Tech Landmarks 

There are a lot of disciplines in the tech world that go beyond web development and data management. Here are a few of them: 

Cloud Computing 

Leading by example, AWS had established cloud computing as the on-demand delivery of IT resources and applications via web services/Internet over a decade considering all layers to make it easy from servers up to top most layer. This will enable organizations to consume technology resources in the form of pay-as-you-go model without having to purchase, own and feed that infrastructure. JOIN US

Cloud Computing Advantages:  

Main advantages are cost savings, scalability, flexibility and disaster recovery. Resources can be scaled based on usage, which means companies only pay for what they are using and have the data backed up in case of an emergency. 

Examples of Cloud Services: 

Few popular cloud services are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. These provide a plethora of services that helps to Develop and Manage App, Store Data etc. 

Cybersecurity 

As the world continues to rely more heavily on digital technologies, cybersecurity has never been a bigger issue. Protecting computer systems, networks and data from cyber attacks is called Cyber security. 

Phishing attacks, Malware, Ransomware and Data breaches: 

This is common cybersecurity threats. These threats can bear substantial ramifications, from financial damages to reputation harm for any corporation. 

Cybersecurity Best Practices:  

In order to safeguard against cybersecurity threats, it is necessary to follow best-practices including using strong passwords and two-factor authorization, updating software as required, training employees on security risks. 

Artificial Intelligence and Machine Learning 

Artificial Intelligence (AI) and Machine Learning (ML) represent the fastest-growing fields of creating systems that learn from data, identifying patterns in them. These are applied to several use-cases like self driving cars, personalization in Netflix. 

AI vs ML —  

AI is the broader concept of machines being able to carry out tasks in a way we would consider “smart”. Machine learning is a type of Artificial Intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. JOIN US

Applications of Artificial Intelligence and Machine Learning: some common applications include Image recognition, Speech to text, Natural language processing, Predictive analytics Robotics. 

Web Development meets Data Management etc. 

We need so many things like web development, data management and cloud computing plus cybersecurity etc.. but some of them are most important aspects i.e. AI/ML yet more fascinating is where these fields converge or play off each other. 

Web Development and Data Management 

Web Development and Data Management goes hand in hand. The large number of websites and web-based applications in the world generate enormous amounts of data — from user interactions, to transaction records. Being able to manage this data is key in providing a fantastic user experience and enabling you to make decisions based on the right kind of information. 

E.g. E-commerce Website, products data need to be saved on server also customers data should save in a database loosely coupled with orders and payments. This data is necessary for customization of the shopping experience as well as inventory management and fraud prevention. 

Cloud Computing and Web Development 

The development of the web has been revolutionized by cloud computing which gives developers a way to allocate, deploy and scale applications more or less without service friction. Developers now can host applications and data in cloud services instead of investing for physical servers. 

E.g. A start-up company can use cloud services to roll out the web application globally in order for all users worldwide could browse it without waiting due unavailability of geolocation prohibited access. 

The Future of Cybersecurity and Data Management 

Which makes Cybersecurity a very important part of the Data management. The more data collected and stored by an organization, the greater a target it becomes for cyber threats. It is important to secure this data using robust cybersecurity measures, so that sensitive information remains intact and customer trust does not weaken. JOIN US

Ex: A healthcare provider would have to protect patient data in order to be compliant with regulations such as HIPAA (Health Insurance Portability and Accountability Act) that is also responsible for ensuring a degree of confidentiality between a provider and their patients. 

Conclusion 

Well, in a nutshell web-developer or Data manager etc are some of the integral parts for digital world.

As a Business Owner, Tech Enthusiast or even if you are just planning to make your Career in tech — it is important that you understand these. With the progress of technology never slowing down, these intersections are perhaps only going to come together more strongly and develop into cornerstones that define how we live in a digital world tomorrow. 

With the fundamental knowledge of web development, data management, automation and ML you will manage to catch up with digital movements. Whether you have a site to build, ideas data to manage or simply interested in what’s hot these days, skills and knowledge around the above will stand good for changing tech world. JOIN US

[hemantrowdy]

Looking for an IT Training Institute Near Me? Choose Code with TLS for Success

If you're searching for an IT Training Institute Near Me, look no further than Code with TLS. As a leading Tech Course Provider, we offer a wide range of industry-relevant courses designed to help you gain the skills needed for a successful career in technology. Whether you're looking to switch careers, upskill, or start fresh in the tech world, Code with TLS is the perfect choice to help you achieve your goals.

Why Choose Code with TLS?

At Code with TLS, we understand that the right IT training can make all the difference in your career. That's why we provide top-tier courses that not only focus on the technical skills needed in today’s job market but also emphasize practical, hands-on learning. Our training programs are tailored to meet the needs of both beginners and professionals looking to advance in their careers.

As an IT Training Institute Near Me, we offer the following benefits:

Industry-Relevant Courses: From Digital Marketing and MERN Stack Development to Data Science and AI/ML, we provide courses that align with current industry trends and demand. Our curriculum is designed to ensure you gain expertise in the latest technologies.

Experienced Instructors: Learn from highly skilled professionals who bring real-world experience to the classroom. Our instructors are passionate about teaching and dedicated to helping you succeed.

100% Placement Assistance: One of the biggest challenges after completing training is securing a job. At Code with TLS, we help our students land their dream jobs through our 100% placement assistance program. We have partnered with over 650 companies to help students find the best opportunities.

Flexible Learning Options: Whether you prefer online courses or need an in-person classroom experience, we have flexible learning options to suit your schedule and preferences.

Personalized Support: Our team is always available to provide guidance and support throughout your training journey, ensuring you get the most out of your learning experience.

Start Your Tech Journey Today!

If you're ready to take the next step in your career and join one of the best IT Training Institutes Near Me, Code with TLS is here to help you succeed. Our expert instructors, comprehensive courses, and dedicated placement assistance will give you the edge you need to thrive in the tech industry.

Contact us today at +918527866980 to learn more about our courses and enroll in the program that suits your career goals. Let's make your tech dreams a reality!

[nearlearn6]

Discover how Machine Learning is shaping the modern world! This infographic explores 5 powerful real-world applications of Machine Learning across industries like healthcare, finance, transportation, and more. From fraud detection to self-driving cars, these examples show how ML is driving innovation and solving real-world problems.

Whether you're a tech enthusiast, student, or professional, this infographic offers a quick and visual insight into the practical power of Machine Learning.

🔍 Learn how you can master these skills with industry-relevant training at Nearlearn — a trusted name in AI & ML education.

Checkout the nearlearn website :https://nearlearn.com/courses/ai-and-machine-learning/machine-learning-with-python-training

[jcmarchi]

Andy Nightingale, VP of Product Marketing at Arteris – Interview Series

New Post has been published on https://thedigitalinsider.com/andy-nightingale-vp-of-product-marketing-at-arteris-interview-series/

Andy Nightingale, VP of Product Marketing at Arteris – Interview Series

Andy Nightingale, VP of Product Marketing at Arteris is a seasoned global business leader with a diverse background in engineering and product marketing. He’s a Chartered Member of the British Computer Society and the Chartered Institute of Marketing, and has over 35 years of experience in the high-tech industry.

Throughout his career, Andy has held a range of roles, including engineering and product management positions at Arm, where he spent 23 years. In his current role as VP of product marketing at Arteris, Andy oversees the Magillem system-on-chip deployment tooling and FlexNoC and Ncore network-on-chip products.

Arteris is a catalyst for system-on-chip (SoC) innovation as the leading provider of semiconductor system IP for the acceleration of SoC development. Arteris Network-on-Chip (NoC) interconnect intellectual property (IP) and SoC integration technology enable higher product performance with lower power consumption and faster time to market, delivering proven flexibility and better economics for system and semiconductor companies, so innovative brands are free to dream up what comes next.

With your extensive experience at Arm and now leading product management at Arteris, how has your perspective on the evolution of semiconductor IP and interconnect technologies changed over the years? What key trends excite you the most today?

It’s been an extraordinary journey—from my early days writing test benches for ASICs at Arm to helping shape product strategy at Arteris, where we’re at the forefront of interconnect IP innovation. Back in 1999, system complexity rapidly accelerated, but the focus was still primarily on processor performance and essential SoC integration. Verification methodologies were evolving, but interconnect was often seen as a fixed infrastructure—necessary but not strategic.

Fast-forward to today and interconnect IP has become a critical enabler of SoC (System-on-Chip) scalability, power efficiency, and AI/ML performance. The rise of chiplets, domain-specific accelerators, and multi-die architectures has placed immense pressure on interconnect technologies to become more adaptive, innovative, physically, and software-aware.

One of the most exciting trends I see is the convergence of AI and interconnect design. At Arteris, we’re exploring how machine learning can optimize NoC (Network-on-Chip) topologies, intelligently route data traffic, and even anticipate congestion to improve real-time performance. This is not just about speed—it’s about making systems more innovative and responsive.

What excites me is how semiconductor IP is becoming more accessible to AI innovators. With high-level SoC configuration IP and abstraction layers, startups in automotive, robotics, and edge AI can now leverage advanced interconnect architectures without needing a deep background in RTL design. That democratization of capability is enormous.

Another key shift is the role of virtual prototyping and system-level modeling. Having worked on ESL (Electronic System Level) tools early in my career, it’s rewarding to see those methodologies now enabling early AI workload evaluation, performance prediction, and architectural trade-offs long before silicon is taped out.

Ultimately, the future of AI depends on how efficiently we move data—not just how fast we process it. That’s why I believe the evolution of interconnect IP is central to the next generation of intelligent systems. Arteris’ FlexGen leverages AI driven automation and machine learning to automate NoC (Network-on-Chip) topology generation. How do you see AI’s role evolving in chip design over the next five years?

AI is fundamentally transforming chip design, and over the next five years, its role will only deepen—from productivity aid to intelligent design partner. At Arteris, we’re already living that future with FlexGen, where AI, formal methods, and machine learning are central to automating Network-on-Chip (NoC) topology optimization and SoC integration workflows.

What sets FlexGen apart is its blend of ML algorithms—all combined to initialize floorplans from images, generate topologies, configure clocks, reduce Clock Domain Crossings, and optimize the connectivity topology and its placement and routing bandwidth, streamlining communication between IP blocks. Moreover, this is all done deterministically, meaning that results can be replicated and incremental adjustments made, enabling predictable best-in-class results for use cases ranging from AI assistance for an expert SoC designer to creating the right NoC for a novice.

Over the next five years, AI’s role in chip design will shift from assisting human designers to co-designing and co-optimizing with them—learning from every iteration, navigating design complexity in real-time, and ultimately accelerating the delivery of AI-ready chips. We see AI not just making chips faster but making faster chips smarter.

The semiconductor industry is witnessing rapid innovation with AI, HPC, and multi-die architectures. What are the biggest challenges that NoC design needs to solve to keep up with these advancements?

As AI, HPC, and multi-die architectures drive unprecedented complexity, the biggest challenge for NoC design is scalability without sacrificing power, performance, or time to market. Today’s chips feature tens to hundreds of IP blocks, each with different bandwidth, latency, and power needs. Managing this diversity—across multiple dies, voltage domains, and clock domains—requires NoC solutions that go far beyond manual methods.

NoC solution technologies such as FlexGen help address key bottlenecks: minimizing wire length, maximizing bandwidth, aligning with physical constraints, and doing everything with speed and repeatability.

The future of NoC must also be automation-first and AI-enabled, with tools that can adapt to evolving floorplans, chipset-based architectures, and late-stage changes without requiring complete rework. This is the only way to keep pace with modern SoCs’ massive design cycles and heterogeneous demands and ensure efficient, scalable connectivity at the heart of next-gen semiconductors.

The AI chipset market is projected to grow significantly. How does Arteris position itself to support the increasing demands of AI workloads, and what unique advantages does FlexGen offer in this space?

Arteris is not only uniquely positioned to support the AI chiplet market but has been doing this already for years by delivering automated, scalable Network-on-Chip (NoC) IP solutions purpose-built for the demands of AI workloads including Generative AI and Large Language Models (LLM) compute —supporting high bandwidth, low latency, and power efficiency across increasingly complex architectures.  FlexGen, as the newest addition to the Arteris NoC IP lineup, will play an even more significant role in rapidly creating optimal topologies best suited for different large-scale, heterogeneous SoCs.

FlexGen offers incremental design, partial completion mode, and advanced pathfinding to dynamically optimize NoC configurations without complete redesigns—critical for AI chips that evolve throughout development.

Our customers are already building Arteris technology into multi-die and chiplet-based systems, efficiently routing traffic while respecting floorplan and clock domain constraints on each chiplet. Non-coherent multi-die connectivity is supported over industry-standard interfaces provided by third- party controllers.

As AI chip complexity grows, so does the need for automation, adaptability, and speed. FlexGen delivers all three, helping teams build smarter interconnects—faster—so they can focus on what matters: advancing AI performance at scale.

With the rise of RISC-V and custom silicon for AI, how does Arteris’ approach to NoC design differ from traditional interconnect architectures?

Traditional interconnect architectures were primarily built for fixed-function designs, but today’s RISC-V and custom AI silicon demand a more configurable, scalable, and automated approach than a modified one-size-fits-all solution. That’s where Arteris stands apart. Our NoC IP, especially with FlexGen, is designed to adapt to the diversity and modularity of modern SoCs, including custom cores, accelerators, and chiplets, as mentioned above.

FlexGen enables designers to generate and optimize topologies that reflect unique workload characteristics, whether low-latency paths for AI inference or high-bandwidth routes for shared memory across RISC-V clusters. Unlike static interconnects, FlexGen’s algorithms tailor each NoC to the chip’s architecture across clock domains, voltage islands, and floorplan constraints.

As a result, Arteris enables teams building custom silicon to move faster, reduce risk, and get the most from their highly differentiated designs—something traditional interconnects weren’t built to handle.

FlexGen claims a 10x improvement in design iteration speed. Can you walk us through how this automation reduces complexity and accelerates time-to-market for System-on-Chip (SoC) designers?

FlexGen delivers a 10x improvement in design iteration speed by automating some of the most complex and time-consuming tasks in NoC design. Instead of manually configuring topologies, resolving clock domains, or optimizing routes, designers use FlexGen’s physically aware, AI-powered engine to handle these in hours (or less)—tasks that traditionally took weeks.

As mentioned above, partial completion mode can automatically finish even partially completed designs, preserving manual intent while accelerating timing closure.

The result is a faster, more accurate, and easier-to-iterate design flow, enabling SoC teams to explore more architectural options, respond to late-stage changes, and get to market faster—with higher-quality results and less risk of costly rework.

One of FlexGen’s standout features is wire length reduction, which improves power efficiency. How does this impact overall chip performance, particularly in power-sensitive applications like edge AI and mobile computing?

Wire length directly impacts power consumption, latency, and overall chip efficiency—both in cloud AI / HPC applications that use the more advanced nodes and edge AI inference applications where every milliwatt matters. FlexGen’s ability to automatically minimize wire length—often up to 30%—means shorter data paths, reduced capacitance, and less dynamic power draw.

In real-world terms, this translates to lower heat generation, longer battery life, and better performance-per-watt, all of which are critical for AI workloads at the edge or in mobile environments and the cloud by directly impacting the total cost of ownership (TCO). By optimizing the NoC topology with AI-guided placement and routing, FlexGen ensures that performance targets are met without sacrificing power efficiency—making it an ideal fit for today and tomorrow’s energy-sensitive designs.

Arteris has partnered with leading semiconductor companies in AI data centers, automotive, consumer, communications, and industrial electronics. Can you share insights on how FlexGen is being adopted across these industries?

Arteris NoC IP sees strong adoption across all markets, particularly for high-end, more advanced chiplets and SoCs. That is because it addresses each sector’s top challenges: performance, power efficiency, and design complexity while preserving the core functionality and area constraints.

In automotive, for example, companies like Dream Chip use FlexGen to speed up the intersection of AI and Safety for autonomous driving by leveraging Arteris for their ADAS SoC design while meeting strict power and safety constraints. FlexGen’s smart NoC optimization and generation in data centers help manage massive bandwidth demands and scalability, especially for AI training and overall acceleration workloads.

FlexGen provides a fast, repeatable path to optimized NoC architectures for industrial electronics, where design cycles are tight and product longevity is key. Customers value its incremental design flow, AI-based optimization, and ability to adapt quickly to evolving requirements, making FlexGen a cornerstone for next-generation SoC development.

The semiconductor supply chain has faced significant disruptions in recent years. How is Arteris adapting its strategy to ensure Network-on-Chip (NoC) solutions remain accessible and scalable despite these challenges?

Arteris responds to supply chain disruptions by doubling down on what makes our NoC solutions resilient and scalable: automation, flexibility, and ecosystem compatibility.

FlexGen helps customers design faster and remain more agile to adjust to changing silicon availability, node shifts, or packaging strategies. Whether they are doing derivative designs or creating new interconnects from scratch.

We also support customers with different process nodes, IP vendors, and design environments, ensuring customers can deploy Arteris solutions regardless of their foundry, EDA tools, or SoC architecture.

By reducing dependency on any one part of the supply chain and enabling faster, iterative design, we’re helping customers derisk their designs and stay on schedule —even in uncertain times.

Looking ahead, what are the biggest shifts you anticipate in SoC development, and how is Arteris preparing for them?

One of the most significant shifts in SoC development is the move toward heterogeneous architectures, chiplet-based designs, and AI-centric workloads. These trends demand far more flexible, scalable, and intelligent interconnects—something traditional methods can’t keep up with.

Arteris is preparing by investing in AI-driven automation, as seen in FlexGen, and expanding support for multi-die systems, complex clock/power domains, and late-stage floorplan changes. We’re also focused on enabling incremental design, faster iteration, and seamless IP integration—so our customers can keep pace with shrinking development cycles and rising complexity.

Our goal is to ensure SoC (and chiplet) teams stay agile, whether they’re building for edge AI, cloud AI, or anything in between, all while providing the best power, performance, and area (PPA) no matter the complexity of the design, XPU architecture, and foundry node used.

Thank you for the great interview, readers who wish to learn more should visit Arteris. 

[anupblogs]

[it-training-in-pune]

🎉 𝐂𝐨𝐧𝐠𝐫𝐚𝐭𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐭𝐨 Shekhar Gaikwad🎉 We are thrilled to announce that Shekhar Gaikwad, one of our talented students, has been successfully placed as a Data Scientist Engineer at Monarch Solutions Pvt. Ltd.! 🚀 This achievement reflects Akash’s hard work, dedication, and the expertise gained during his journey with Ethans Tech. A big shoutout to our amazing placement team, Bhavik Mistry and Khushi Patil, for their continuous efforts in making dreams come true! 🙌 Visit us: https://ethans.co.in/

[diptisinghblog]

Unlocking Career Opportunities with PGDM Specialization in AI & ML

[ananyamehtablog]

PGDM in Artificial Intelligence and Machine Learning: Your Path to a High-Tech Career

[classroomlearning]

BTech CSE: Your Gateway to High-Demand Tech Careers

Apply now for admission and avail the Early Bird Offer

In the digital age, a BTech in Computer Science & Engineering (CSE) is one of the most sought-after degrees, offering unmatched career opportunities across industries. From software development to artificial intelligence, the possibilities are endless for CSE graduates.

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Software Developer: Design and develop innovative applications and systems.

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Cloud Architect: Build and maintain cloud-based infrastructure for global organizations.

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Your journey to becoming a tech leader starts here!

[cybersuccesss]

Elevate Your Data Science Skills with Data Science Course in Pune

Success in the rapidly evolving field of data science hinges on one key factor: quality data. Before diving into more complex machine learning algorithms and detailed analysis, starting with a clean data set is important. At The Cyber Success Institute, our Data Science Course in Pune emphasizes mastering these core skills, equipping you with the expertise to handle data efficiently and drive impactful results. These basic data cleaning steps, known as data wrangling and preprocessing, are necessary to process raw data in sophisticated ways that support accurate analysis and prediction to hone these basic skills to process data thoroughly and prepare amazing results A resource that gives you essential knowledge.

Transform Your Career with The Best Data Science Course at Cyber Success

Data wrangling, or data manging, is the process of transforming and processing raw data from its often messy origin into a more usable form. This process involves preparing, organizing, and enhancing data to make it more valuable for analysis and modeling. Preprocessing, which is less controversial, focuses primarily on preparing data for machine learning models to normalize, transform, and scale them to improve performance

At the Cyber ​​Success Institute, we understand that strong data disputes are the cornerstone of any data science project. Our Data Science Course in Pune offers hands-on training in data wrangling and pre-processing, enabling you to effectively transform raw data into actionable insights.

Discover Data Cleaning Excellence with The Best Data Science Course at Cyber Success

The data management process involves preparing, organizing, and enhancing the data to make it more valuable for analysis and modeling. Less controversial preprocessing focuses on data preparation for machine learning models to ensure performance data quality will directly affect the accuracy and reliability of machine learning models The information is well suited and ensures insights are accurate and useful. This helps to identify hidden patterns and saves time during sample development and subsequent analysis. At Cyber ​​Success Institute, we focus on the importance of data security requirements so we prepare you and your employees to ensure that your data is always up to date. Our Data Science Course in Pune offers hands-on training in data wrangling and pre-processing, enabling you to effectively transform raw data into actionable insights. Basic Steps in Data Management and Preprocessing,

Data cleaning: This first and most important step includes handling missing values, eliminating inconsistencies, and eliminating redundant data points. Effective data cleaning ensures that the dataset is reliable, it is accurate and ready for analysis.

Data conversion: Once prepared, the data must be converted to usable form. This may involve converting categorical variables into numeric ones using techniques such as one-hot encoding or label encoding. Normalization and standardization are used to ensure that all factors contribute to the equality of the model, with no feature dominating due to scale differences make sure you are prepared to handle a variety of data environments.

Feature Engineering: Feature engineering is the process of creating new features from existing data to better capture underlying patterns. This may involve forming interactive phrases, setting attributes, or decomposing timestamps into more meaningful objects such as "day of the week" or "hour of the day".

Data reduction: Sometimes data sets can have too many or too many dimensions, which can lead to overqualification or computational costs. Data reduction techniques such as principal component analysis (PCA), feature selection, and dimensionality reduction are essential to simplify data sets while preserving valuable information Our Data Science Classes in Pune with Placement at the Cyber ​​Success Institute provide valuable experience in data reduction techniques to help you manage large data sets effectively.

Data integration and consolidation: Often, data from multiple sources must be combined to obtain complete data. Data integration involves combining data from databases or files into a combined data set. In our Data Science Course in Pune, you will learn how to combine different types of data to improve and increase the relevance and depth of research.

Why Choose Cyber Success Institute for Data Science Course in Pune?

The Cyber ​​Success Institute is the best IT training institute in Pune, India, offering the best data science course in Pune with Placement assistance, designed to give you a deep understanding of data science from data collection to preprocessing to advanced machine learning. With hands-on experience, expert guidance and a curriculum that is up to date with the latest industry trends, you will be ready to become a data scientist

Here are the highlights of the data science course at Cyber ​​Success Institute, Pune:

Experienced Trainers: Our data science expert trainers bring a wealth of experience in the field of data science, including advanced degrees, industry certifications, strong backgrounds in data analytics, machine learning, AI, and hands-on experience in real-world projects to ensure students learn Entrepreneurs who understand business needs.

Advanced Curriculum: Our Data Science Course in Pune is well structured to cover basic and advanced topics in data science, including Python programming, statistics, data visualization, machine learning, deep learning natural language processing and big data technology.

Free Aptitude Sessions: We believe that strong analytical and problem-solving skills are essential in data science. To support technical training, we offer free aptitude sessions that focus on developing logical reasoning, statistical analysis and critical thinking.

Weekly Mock Interview Sessions: To prepare you for the job, we conduct weekly mock interview sessions that simulate real-world interview situations. These sessions include technical quizzes on data science concepts, coding problems, and behavioral quizzes to build student confidence and improve interview performance.

Hands-on Learning: Our Data Science Course in Pune emphasizes practical, hands-on learning. You will work on real-world projects, data manipulation, machine learning model development, and applications using tools such as Python and Tableau. This approach ensures a deep and practical understanding of data science, preparing them for real job challenges.

100% Placement Assistance: We provide comprehensive placement assistance to help you start your career in data science. This includes writing a resume, preparing for an interview, and connecting with potential employers.

At Cyber Success, our Data Science Course in Pune ensures that students receive a well-rounded education that combines theoretical knowledge with practical experience. We are committed to helping our students become skilled, confident and career-ready data scientists.

Conclusion:

Data management and preprocessing are the unsung heroes of data science, transforming raw data into powerful insights that shape the future. At Cyber Success Institute, our Data Science Course in Pune will teach you the technical skills and it will empower you to lead the data revolution. With immersive, hands-on training, real-world projects, and mentorship from industry experts, we prepare you to harness data’s full potential and drive meaningful impact. Joining Cyber Success Institute, it’s about becoming part of a community committed to excellence and innovation. Start your journey here, master the art of data science with our Data Science Course in Pune, and become a change-maker in this rapidly growing field. Elevate your career, lead with data, and let Cyber Success Institute be your launchpad to success. Your future in data science starts now!

Attend 2 free demo sessions!

To learn more about our course at, https://www.cybersuccess.biz/data-science-course-in-pune/

Secure your place at, https://www.cybersuccess.biz/contact-us/

📍 Our Visit: Cyber Success, Asmani Plaza, 1248 A, opp. Cafe Goodluck, Pulachi Wadi, Deccan Gymkhana, Pune, Maharashtra 411004

📞 For more information, call: 9226913502, 9168665644, 7620686761.

PATH TO SUCCESS - CYBER SUCCESS 👍

[hemantrowdy]

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Junyoung Lee, President of Technology & Yanolja Group CTO, Co-CEO at Yanolja Cloud – Interview Series

New Post has been published on https://thedigitalinsider.com/junyoung-lee-president-of-technology-yanolja-group-cto-co-ceo-at-yanolja-cloud-interview-series/

Junyoung Lee, President of Technology & Yanolja Group CTO, Co-CEO at Yanolja Cloud – Interview Series

Junyoung Lee is the President of Technology and Group Chief Technology Officer (CTO) at Yanolja, as well as the co-CEO of Yanolja Cloud. With a career spanning over two decades, he is a highly respected leader in the technology and software engineering space.

Since joining Yanolja in May 2022, Junyoung has played a pivotal role in driving the company’s digital transformation and global technology strategy. Initially serving as Executive Vice President of Engineering, he was instrumental in advancing Yanolja’s technological innovation. In April 2023, he was appointed co-CEO of Yanolja Cloud, where he leads the development of cutting-edge SaaS solutions for the travel and hospitality industry. In April 2024, he took on the role of President of Technology and Group CTO, further reinforcing Yanolja’s position as a global tech leader.

Prior to Yanolja, Junyoung had a distinguished career at Google, where he served as a Software Engineering Director for nearly 20 years. He was the first employee at Google Korea, establishing its R&D team and spearheading the company’s engineering development programs.

Yanolja is Korea’s leading online travel agency (OTA) which offers all travel and experience related services to make travel comfortable and enjoyable for everyone. Yanolja Cloud is a hospitality solutions company specializing in user-friendly and integrated cloud-based technologies tailored for the hospitality sector, targeting customers worldwide.

You’ve had an incredible journey from Google to Yanolja, including a role in setting up Google Korea. What motivated you to transition from a tech giant to a rapidly growing company like Yanolja?

My journey began as the first Korean native speaker hired at Google HQ in California, where I later helped set up Google Korea. Over two decades at Google, I witnessed how data and technology can transform lives and drive meaningful innovation. Yet, as impactful as these advancements were, the travel industry had lagged behind in adopting cutting-edge technology.

When I met Sujin Lee, Yanolja’s founder, his vision of addressing the inefficiencies and challenges in travel struck a chord. Travel involves dreaming, planning, booking, and sharing—processes that generate immense amounts of data. However, this data has remained largely underutilized. Yanolja’s commitment to leveraging AI and advanced data platforms to improve these experiences was inspiring. It was a unique opportunity to join a company at the forefront of transforming an entire industry.

Yanolja’s bold vision, powered by AI and our proprietary data lake, allows us to refine and augment data to create Vertical AI solutions tailored for the travel and hospitality sectors. This approach not only enhances operational efficiency but also redefines customer experiences, positioning Yanolja as a global leader in travel tech.

As a leader in the AI space, what lessons from Google and your previous roles have been most impactful in shaping your approach to driving AI innovation at Yanolja?

Two key lessons have shaped my approach. First, technology needs to be human-centered. The pace of innovation often outstrips people’s ability to adapt, so intuitive design is critical for broader adoption. Second, data is the foundation of AI. If data is incomplete or flawed, AI outcomes can be inaccurate or even harmful, much like a child acting on misleading experiences.

At Yanolja, we prioritize data integrity across the entire travel value chain. By ensuring that the data flowing through our systems is accurate, we deliver secure, transparent solutions for both our B2B partners and end customers. This is where Yanolja’s Vertical AI approach becomes critical—we specialize in AI solutions tailored for the travel industry, driving measurable results that directly enhance profitability and customer satisfaction.

How has your experience working across different countries and tech ecosystems (South Korea, Silicon Valley) influenced your leadership style and vision for technology?

At Google in Silicon Valley, I collaborated with teams from around the world on global services, which taught me the importance of aligning diverse teams toward a common goal. At Yanolja, I now lead R&D teams across Korea, India, Israel, and Europe, uniting them as “One Yanolja Team” to drive innovation and execute projects collaboratively.

My Silicon Valley experience reinforced the need to balance short-term business priorities with long-term technological investments. While immediate solutions address pressing challenges, sustainable innovation requires foundational work. At Yanolja, we integrate data and AI to tackle today’s business needs while building a platform for future leadership in the travel tech industry.

How is Yanolja leveraging AI to transform the travel and hospitality industry, particularly in areas like operational efficiency and customer experience?

The travel industry has long been slow to embrace technological change. Many operations in hospitality and booking are still manual or inefficient, limiting both productivity and potential growth. At Yanolja, we’ve introduced AI-driven solutions to address these gaps.

For example, our Dynamic Pricing solution uses AI and machine learning (ML) to automate real-time price adjustments, directly impacting hotel revenues by replacing manual processes with smarter, data-driven decisions. Similarly, our AI-powered travel planning services offer personalized itineraries and optimized travel routes, enhancing customer experiences.

Beyond these examples, Yanolja applies AI across customer service, marketing, workflow optimization, and product development. Our Vertical AI solutions are tailored to meet the unique needs of travel businesses, enabling us to lead the industry’s transformation by creating innovative, efficient, and customer-centric systems.

Yanolja operates in over 200 countries. What challenges and opportunities come with scaling AI solutions for such a diverse global audience?

Scaling AI solutions globally requires understanding diverse market needs while leveraging shared insights. For example, our Dynamic Pricing AI adapts seamlessly to markets like South Africa, India, and Korea using a single model that identifies universal pricing patterns from our data lake.

One significant challenge is overcoming language barriers. To address this, we’ve developed AI-powered tools like context-aware image translations, enabling non-Korean speakers to access localized content in English, Japanese and Chinese. Today, Yanolja supports over 60 languages, reflecting our commitment to inclusivity and global accessibility.

Yanolja offers an integrated suite of solutions like cloud PMS, booking engines, and payment systems. Can you share insights into how these systems use AI to enhance productivity and personalization?

We’ve integrated AI into our cloud-based hotel management system (PMS) to streamline operations. For instance, our AI interface allows hotel managers to query tasks like room assignments or operational reports conversationally, simplifying complex processes.

Additionally, AI-powered customer service tools help us automate the classification and prioritization of inquiries, reducing response times by 40%. These innovations, combined with our Vertical AI solutions, ensure operational efficiency and personalization for all stakeholders.

How does Yanolja’s proprietary Data Lake help unlock new AI applications, and what role does data quality play in the success of your solutions?

AI continues to unlock the potential of underutilized data, transforming online travel agencies (OTAs) into hyper-personalized travel agents and enhancing customer experiences. Yanolja’s focus on Vertical AI ensures our solutions deliver measurable impact, setting us apart as leaders in the evolving travel ecosystem.

As we look ahead, we envision AI not just optimizing travel bookings or itineraries but enabling fully integrated, seamless travel experiences. AI-driven insights will empower businesses to predict and meet customer needs more effectively, ensuring every aspect of a traveler’s journey is personalized and optimized. To achieve this, Yanolja is building a travel data platform tailored for the industry, incorporating connectivity, a single source of truth via a data lake, and AI/ML-based data technologies—all of which are critical to maintaining data quality and unlocking new applications.

What trends do you see shaping the future of AI in the travel industry, and how is Yanolja positioning itself to lead in this space?

AI is poised to revolutionize the travel industry by unlocking the vast potential of underutilized data. Over the next decade, we will see a shift from simple booking platforms to highly sophisticated, AI-driven agents that provide hyper-personalized travel experiences. These AI agents will not only help travelers plan but will also assist in real-time decision-making during their journey.

At Yanolja, we are at the forefront of this transformation by focusing on Vertical AI—creating specialized applications that address the unique challenges of the travel industry. Our data-driven solutions are already helping businesses optimize operations, personalize services, and ultimately enhance customer satisfaction.

The future will also see greater integration of AI across the entire travel journey, from the moment a customer dreams about their trip to when they share their experience post-trip. We are positioning ourselves to lead this change by investing heavily in AI capabilities that will continue to disrupt and redefine how the travel industry operates.

As someone who built and managed teams at Google Korea and now Yanolja, what advice do you have for fostering innovation and collaboration in tech teams?

First and foremost, it’s important to have a clear and sustainable vision and mission for what we aim to achieve with technology. Each person brings unique strengths to the table. However, no matter how talented a group of people is, if they are not aligned in their direction, they risk falling behind in the rapidly changing external environment of the AI era. I believe that what’s needed today is not one genius who can’t collaborate, but a team of 10 individuals with exceptional teamwork. It’s about taking 10 pieces of wood—each different in shape, size, and color—and turning them into a unique masterpiece. The ultimate goal is to create something that improves the lives of people around the world. This, I believe, is the role of tech teams in the AI era.

Where do you see Yanolja in the next 5–10 years, particularly in its quest to become a global leader in travel technology?

Leaving a well-established company in Silicon Valley to join Yanolja was driven by my goal to disrupt the travel industry globally as a tech company, leveraging data. That process is already underway, and the pace is accelerating. At the core of this transformation is AI. Innovation through technology is reshaping the world, and as a tech executive, it is my role and responsibility to ensure that AI-driven solutions create services that meet customer needs and ultimately drive Yanolja’s success.

Looking ahead, Yanolja aims to be the foundation for global travel innovation, leveraging our Vertical AI capabilities to build a unified, efficient travel ecosystem. Over the next decade, we envision our AI-driven solutions not only enhancing operational efficiencies but also creating entirely new ways for businesses and consumers to experience travel, disrupting the industry in ways we’ve only just begun to explore.

Thank you for the great interview, readers who wish to learn more should visit Yanolja or Yanolja Cloud.

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Artificial Intelligence in Mechanical Engineering - CGC Jhanjeri

Mechanical Engineering with AI aids tasks, yet complete replacement is doubtful. AI enhances design, analysis, and optimization efficiency, but human skills remain vital for complex choices, hands-on work, and real-world fixes. AI serves as a tool, automating routines and empowering engineers to innovate, nurturing a harmonious AI-Mechanical Engineering partnership.