Gradious’ Post

Machine learning opens a window for mid-career job opportunities with more and more businesses across industries adopting automation and leveraging data to grow, a career in machine learning (ML) seems promising. Considered a division of artificial intelligence, this field has become an attractive career pathway not only for freshers but for mid-career professionals as well. ML learning is gaining prominence in areas such as customer insights and personalisation, operational efficiency, fraud detection and security, customer service and support, sales and marketing, human resources, product development, financial forecasting and management ML engineers, data scientists, AI research scientists and product managers are some of the roles seeing a surge in demand.

🚨 ALERT Post 🚨 🔍People on LinkedIn say that having a college degree won't help you get a Job. And some influencers posted 12th passed out getting Data Scientist/AI ML Engineer jobs by learning from Youtube. One of the most misguided influences ever. 🎓 To be honest, people with a Master's degree struggle to crack those roles. I have seen a bright candidate with enough skills struggle to get Data Science, ML, and AI roles as freshers. 🧮 "Only 6th standard Math is enough for DS, ML, AI roles"- biggest lie ever. If you start to study basic neural networks- you will get to know how much math is involved. (Engineering Mathematics helped me a lot) 🗣️"I heard an Influencer saying we trained(Data Science) the 12th standard kid and we placed him for 4LPA "- Biggest Lie ever. 📚Still having a College degree will help you in many things. Subjects and skills are temporary. Learning is permanent. 📢 #DataScience #ML #AI #EducationMatters 🎓

💡𝐈𝐬 𝐂𝐨𝐝𝐢𝐧𝐠 𝐍𝐞𝐜𝐞𝐬𝐬𝐚𝐫𝐲 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐀𝐈?🤔 In this video, we explore the common question: "Is coding a must to start your AI journey?" The answer may surprise you! While coding isn't essential initially, mastering it later becomes crucial to excel and dive deeper into the complexities of AI development. 🌟 Discover how foundational knowledge can get you started in AI, and how adding coding skills later can unlock top-tier roles in companies like Google, Amazon, and Microsoft. At Ethans Tech🎓, our AI courses are designed to guide you step-by-step—from beginner concepts to advanced coding—ensuring you're fully prepared for a future in AI! 🚀 Visit Us: https://ethans.co.in/ #LinkedInTips #CareerGrowth #AIWithoutCoding #AIJourney #EthansTech #MasterAI #TechCareers #ITCareerBuild #ITTraining #ITTrainingCenter #Pune #fresher #jobs ##itjobs #freshersjobs #DataAnalytics ##DataScience

𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 & 𝐀𝐈 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐒𝐞𝐫𝐢𝐞𝐬: 5 𝐾𝑒𝑦 𝑄𝑢𝑒𝑠𝑡𝑖𝑜𝑛𝑠 𝐴𝑏𝑜𝑢𝑡 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: 𝟏. 𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐭𝐡𝐫𝐞𝐞 𝐦𝐚𝐢𝐧 𝐭𝐲𝐩𝐞𝐬 𝐨𝐟 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠? 𝟐. 𝐂𝐚𝐧 𝐲𝐨𝐮 𝐞𝐱𝐩𝐥𝐚𝐢𝐧 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐢𝐧 𝐝𝐞𝐭𝐚𝐢𝐥 𝐰𝐢𝐭𝐡 𝐚𝐧 𝐞𝐱𝐚𝐦𝐩𝐥𝐞? 𝟑. 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐔𝐧𝐬𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐢𝐬 𝐢𝐭 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐟𝐫𝐨𝐦 𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐞𝐝 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠? 𝟒. 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐝𝐨𝐞𝐬 𝐢𝐭 𝐰𝐨𝐫𝐤? 𝟓. 𝐂𝐚𝐧 𝐲𝐨𝐮 𝐞𝐱𝐩𝐥𝐚𝐢𝐧 𝐚 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐞𝐚𝐜𝐡 𝐭𝐲𝐩𝐞 𝐨𝐟 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠? As freshers and early Data Science and AI career aspirants, this series will help you prepare better for your upcoming roles and interviews. This document help by providing with a comprehensive guide to the three main types of Machine Learning (ML): Supervised, Unsupervised, and Reinforcement Learning. It offers easy and detailed explanations of each type, along with real-world examples and applications, to help them understand the concepts thoroughly. The document also includes detailed explanations of supervised and unsupervised learning, along with their sub-types and common algorithms, which are frequently asked about in Data Science interviews. By studying this guide, freshers and Data Science aspirants can gain a solid understanding of ML fundamentals, enabling them to confidently answer interview questions and showcase their knowledge to potential employers. Hope you find this insightful. #Interviews #DataScience #AI #Freshers #Early #Career #Preparation #MachineLearning #types #supervised #unsupervised #reinforced

BCA (Bachelor of Computer Applications) in AI (Artificial Intelligence) and ML (Machine Learning) offers excellent career prospects in today's technology-driven world. Here are some reasons why it's considered one of the best choices for a career: #High Demand: The demand for AI and ML professionals is rapidly increasing across industries due to the growing adoption of AI technologies for automation, data analysis, predictive modeling, and decision-making. #Diverse Job Opportunities: Graduates can explore various career paths such as AI engineer, data scientist, machine learning specialist, AI solution architect, research analyst, and more. These roles are available in sectors like healthcare, finance, e-commerce, autonomous systems, cybersecurity, and telecommunications. #Competitive Salaries: AI and ML professionals command competitive salaries globally due to their specialized skills and high demand. Companies are willing to offer attractive compensation packages to attract top talent in this field. #Innovation and Impact: Working in AI and ML allows professionals to be at the forefront of technological innovation, solving complex problems, and making a significant impact on businesses, society, and the world at large. #Continuous Learning and Growth: The field of AI and ML is constantly evolving with new advancements, techniques, and tools. This offers professionals continuous learning opportunities and the chance to stay updated with the latest trends, making their careers dynamic and rewarding. #Overall, BCA in AI and ML provides a strong foundation for a successful and fulfilling career in the exciting and rapidly evolving field of artificial intelligence and machine learning. #advertising #ai #futureofwork #linkedingrowth #linkedinforcreators #linkedincreators #linkedin #growth #linkedin #linkedinforcreators #growth #linkedingrowth #linkedincreators #viral #connection #linkedin

🌟 𝗕𝗿𝗲𝗮𝗸𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗛𝗶𝗴𝗵-𝗣𝗮𝘆𝗶𝗻𝗴 𝗔𝗜/𝗠𝗟 𝗥𝗼𝗹𝗲𝘀: 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂 𝗡𝗲𝗲𝗱 𝘁𝗼 𝗞𝗻𝗼𝘄 🌟 The demand for machine learning professionals is at an all-time high as 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗲 𝘁𝗼 𝗶𝗻𝘃𝗲𝘀𝘁 𝗵𝗲𝗮𝘃𝗶𝗹𝘆 𝗶𝗻 𝗔𝗜/𝗠𝗟. One of the most frequent questions I receive from freshers and early-career professionals is: "What skills are essential to land high-paying AI/ML roles?" 𝗔𝗳𝘁𝗲𝗿 𝗿𝗲𝘃𝗶𝗲𝘄𝗶𝗻𝗴 𝗵𝘂𝗻𝗱𝗿𝗲𝗱𝘀 𝗼𝗳 𝗷𝗼𝗯 𝗱𝗲𝘀𝗰𝗿𝗶𝗽𝘁𝗶𝗼𝗻s from companies like NVIDIA, Microsoft etc, here are the top skills that stand out: 🔍 Companies generally fall into two categories: 1️⃣ Big Product-Based MNCs: Core Skills: Classical ML algorithms, Deep Learning fundamentals, Transformers, LSTM, LLMs, Generative AI Technical Proficiency: Easy to medium-level DSA, Python 2️⃣ Startups: Core Skills: Same as above, but with less emphasis on DSA and more on can do it from day 1. Deployment/Monitoring: Docker, Kubernetes, MLflow/Kubeflow Cloud Platforms: GCP, AWS, or Azure (proficiency in any one) ML Frameworks: PyTorch, TensorFlow Above listed are good to have to MNC's at entry level but not essential. Focusing on these skills will help you stand out and succeed in the competitive field of AI/ML. The opportunities are vast—now is the time to prepare and make your mark! If you are looking for personalised guidance on getting started with AI ML or mock interview, do book a session. Link in comments. #AI #MachineLearning #CareerTips #TechCareers #MLSkills

🌟BTech in AI vs. BTech in CSE: Understanding the Difference & Career Prospects Choosing the right engineering specialization is important for your career as technology evolves. Two popular and future-proof options are BTech in Artificial Intelligence (AI) and BTech in Computer Science Engineering (CSE). Here’s a quick breakdown of their differences and career prospects: 1. BTech in Artificial Intelligence (AI) Specializes in AI technologies such as machine learning, deep learning, natural language processing, robotics, and automation. Skills Learned: AI algorithms, data science, neural networks, and predictive modelling. Career Opportunities: AI Engineer, Data Scientist, Machine Learning Engineer, Robotics Specialist, AI Researcher. Industry Demand: High demand in sectors like healthcare, finance, and automotive, and tech giants like Google, Microsoft, and Amazon focus heavily on AI advancements. 2. BTech in Computer Science Engineering (CSE): Offers a broader curriculum that covers a wide range of computing technologies like software development, algorithms, databases, operating systems, and networking. Skills Learned: Programming languages, system architecture, software engineering, and cybersecurity. Career Opportunities: Software Developer, Systems Analyst, Network Engineer, Cybersecurity Specialist, Database Administrator. Industry Demand: CSE graduates have diverse career options across industries such as IT services, tech companies, banking, e-commerce, and more. Key Differences: Specialization vs. Generalization: AI is a specialized field within CSE, while CSE offers broader computing knowledge. Emerging vs. Established Field: AI is a rapidly emerging domain with cutting-edge innovations, while CSE is well-established, offering stability and flexibility across multiple roles. Which One to Choose? Choose BTech in AI if you are passionate about working on the future of technology, creating intelligent systems, and delving into data science and machine learning. If you want a degree that allows you to work in various roles in the IT and tech industries, choose a BTech in CSE. Both degrees offer promising career opportunities, so your choice should be based on your passion. #AI #CSE #BTech #ArtificialIntelligence #Computerscience #Engineeringcareers #Careerprospects #TechInnovation #Futureofwork #Machinelearning #Softwareengineering #Datascience #university #students #admission #btech

These are the 5 most common interview rounds for Data Scientist/ML Engineer/AI Engineer roles: 1. Theory In this round, theories can be asked from Machine Learning, Deep Learning, NLP, Computer Vision, Gen AI. Be also prepared for linear algebra, statistics and probability concepts. 2. Projects This is a crucial part. If any of your project sounds interesting, interviewer will take you to maximum depth. Be prepared with end-to-end implementation details. 3. DSA Although you don't need to be a pro here, you should be able to solve at least easy-medium level problems. Imp topics include hashmap, array, linked list, stack, queue etc. 4. Python skills Not just Python, they want to see how you can handle data. You need to know how to clean, how to find outliers, normalisation, mean, median, mode etc. 5. ML system design For freshers you will be given a problem and expected to come up with a basic ML pipeline. Prepare with data cleaning, model training, model validation and testing. Remember, these are only technical rounds. There could be managerial rounds, HR rounds as well. Now, if you aspire to crack Data roles at top companies, and need a platform to help you ace your interview, I suggest letting the industry veterans at Bosscoder Academy help you. Check the complete program here: https://bit.ly/3Nd0roL They can help you with: ✅ Structured curriculum to learn SQL, Data Visualization, and Machine Learning. ✅ Getting you job-ready for top companies. ✅ Personal mentorship from experienced Data professionals. ✅ Live classes, project-based learning, and access to a talented community of people with similar goals of upskilling. #datascience #machinelearning #ai

🚀Career Awareness: Machine Learning Experts 💭Imagine being a sought-after Machine Learning Expert at top tech firms, leading cutting-edge projects and shaping the future of AI! 💫As a Machine Learning Expert, you'll design and implement complex algorithms to enable machines to learn independently. 💵Salary range for fresher- INR 6-8 Lakhs per annum, experienced- INR 15-20 Lakhs per annum in India. 👨💼Machine Learning has immense scope in India across industries like IT, healthcare, finance, and more. 👩💻Develop proficiency in programming languages like Python, knowledge of statistical concepts, and a strong analytical mindset. #MachineLearning #AI #DataScience #TechCareers #CareerOpportunities

#MachineLearning has emerged as a promising #Careers option, offering #Opportunities for both #fresh #Graduates and #mid-career #professionals, thanks to its wide-ranging #applications in areas like customer insights, operational efficiency, and beyond. The increasing adoption of automation and data-driven strategies by businesses across various industries has further fueled the demand for #ML #skills. Key skills required for a career in ML include proficiency in #python, a solid understanding of statistics, and familiarity with machine learning frameworks. The rise of accessible learning platforms has made it easier for individuals to acquire these skills, paving the way for #CareerGrowth. #Freelance roles in machine learning are also becoming increasingly popular. According to Anesh Korla, EVP & COO of Encora, India, machine learning is gaining traction in diverse fields such as customer insights and personalization, fraud detection and security, customer service and support, sales and marketing, human resources, product development, financial forecasting, and management. This makes it a highly attractive career pathway for professionals at different stages of their #Careers. Visit for Latest Jobs - www.rozgar.com #AI #CareerGrowth #techcareers #python #datasciencee #automation #MLSkills #careerdevelopment #freelancer #artificialintelligence #techindustry #OperationalEfficiency #customerinsights #futureofwork #jobopportunity #jobsearch #rozgar #jobseekers #jobportal #jobvacancy