Suryansh Rana’s Post

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MIT University has released free online courses. Here are their most popular courses to learn new skills in 2024 1. Introduction to Computer Science and Programming Using Python - https://lnkd.in/e6hEBbAw An introduction to computer science as a tool to solve real-world analytical problems using Python 3.5. 2. Introduction to Computational Thinking and Data Science - https://lnkd.in/emMUJ8_P An introduction to using computation to understand real-world phenomena. 3. Machine Learning with Python - https://lnkd.in/eJsi2vg7 An in-depth introduction to the field of machine learning through hands-on Python projects. 4. Supply Chain Analytics - https://lnkd.in/eJztxKuN Master and apply the core methodologies used in supply chain analysis and modeling, including statistics, regression, optimization and probability. 5. Understanding the World Through Data - https://lnkd.in/es55EKsW Become a data explorer – learn how to leverage data and basic machine learning algorithms to understand the world. 6. Becoming an Entrepreneur - https://lnkd.in/eCqW8r_T Learn the business skills and startup mindset needed to embark on your entrepreneurial path. 7. Shaping Work of the Future - https://lnkd.in/eKfCBNa7 Explore ways to improve job opportunities and develop a personal plan for lifelong career success. 8. Foundations of Modern Finance I - https://lnkd.in/eAv6HG8u A mathematically rigorous framework to understand financial markets delivered with data-driven insights from MIT professors. 9. Probability - The Science of Uncertainty and Data - https://lnkd.in/ecju9zwq Build foundational knowledge of data science with this introduction to probabilistic models. 10. Introduction to Biology - The Secret of Life - https://lnkd.in/eiVVvZTq Explore the secret of life through the basics of biochemistry, genetics, molecular biology, recombinant DNA, genomics and rational medicine. ➡ Get tutorials and guides on using popular AI tools for FREE here: https://lnkd.in/ewyJYCPx #ai #artificialintelligence #innovation #technology #tech #productivity #learning #freecourses

Free online courses from MIT #computerscience #python #ml #machinelearning #supplychain #data #datascience #dataanalytics #dataanalysis 

Unlock the World of AI with FREE Courses from Top Universities! 🚀🎓 ♻ Repost to be the hero of your network! No fees, just knowledge: jump into AI with me. Transform your career or personal growth journey without spending a dime! I've selected a list of 10 FREE AI courses from prestigious universities, available to everyone. Here's what you'll discover: Harvard - CS50's Introduction to Artificial Intelligence with Python Fundamentals of TinyML - CS50's Computer Science for Business Professionals IBM - AI for Everyone: Master the Basics MIT - Introduction to Computer Science and Programming Using Python - Machine Learning with Python: from Linear Models to Deep Learning - Data Analysis: Statistical Modeling and Computation in Applications Stanford - Machine Learning Specialization - Statistical Learning with Python - Statistical Learning with R To get this file in high quality: 👊 - Follow - Comment "Courses" - Join my newsletter at aidenis.com And you will get the PDF right away!

🌟 Excited to Share My Latest Achievement! 🌟 I am thrilled to announce that I have successfully completed the Approximation Algorithms and Linear Programming course on Coursera! 🎓📊 This journey has been incredibly rewarding, providing deep insights into advanced optimization techniques and problem-solving strategies. 🚀 Key Learnings and Highlights: Approximation Algorithms: Approximation algorithms are essential when exact solutions are impractical due to time complexity. They provide near-optimal solutions within a factor of the optimal one. 1) Greedy Algorithms: • Set Cover Problem: Learned how to implement greedy strategies to achieve a logarithmic approximation factor. • Vertex Cover Problem: Explored how to cover vertices in graphs effectively, balancing accuracy and performance. 2) Primal-Dual Method: • A fascinating approach that involves simultaneously considering the primal and dual problems to derive approximation solutions. 3) Local Search Algorithms: • Techniques for improving solutions by exploring the neighborhood of the current solution, making iterative improvements. 4) Randomized Algorithms: • Using randomization to achieve approximation guarantees, particularly in problems like Max Cut and randomized rounding techniques. Linear Programming (LP): Linear programming is a powerful mathematical method for optimizing a linear objective function, subject to linear equality and inequality constraints. 1) Formulation: • Learned to formulate real-world problems as linear programs, including resource allocation, production planning, and logistics. 2) Simplex Method: • Explored the simplex algorithm for solving linear programs, understanding its geometric interpretation and pivot operations. 3) Duality Theory: • Delved into the relationship between primal and dual problems, understanding how solutions to one provide insights into the other. 4) Integer Linear Programming (ILP): •Tackled ILP problems where some or all variables are constrained to be integers, using techniques like branch-and-bound and cutting planes. 5) Applications of LP: • Practical applications in various industries, such as transportation, finance, telecommunications, and manufacturing. 💼 Next Steps: 1) Real-World Application: Implementing these algorithms in real-world projects to solve complex optimization problems efficiently. 2) Further Learning: Pursuing advanced courses in combinatorial optimization and advanced LP techniques to deepen my understanding. 3) Collaboration: Connecting with fellow professionals and researchers to collaborate on projects and share insights. 4) Research and Development: Contributing to open-source projects and research papers focusing on optimization and algorithmic strategies. #AlgorithmDesign #LinearProgramming #Optimization #ContinuousLearning #ProfessionalGrowth #Coursera #MachineLearning #DataScience #100DaysOfCode #TechLearning

Recently, my juniors asked me "How should we pursue a career in Artificial Intelligence (AI) and what are the best sources to learn it from basics?" It's a great question, and it made me reflect on the key considerations one should be aware of before diving into this fascinating field. 🤔 Here are some essential things to keep in mind if you're thinking about taking AI as a career: 1) Foundation in Mathematics and Statistics 🔍 : While many people might be intimidated by math and statistics, don't worry—you just need to know the basics in these areas such as linear algebra, calculus, probability, and statistics. This course will give a great start to your AI journey. https://lnkd.in/dMJzg7PS by DeepLearning.AI 2) Programming Skills👨💻: Proficiency in programming languages like Python is essential. Python, in particular, is widely used in AI for its simplicity and extensive libraries like TensorFlow, Keras, and PyTorch. Choose any one language and stick to it. Start with the basics, and learn all the necessary libraries coming along the way. This is what I do and it did help me. 3) Understanding of Algorithms and Data Structures: Knowledge of algorithms and data structures is fundamental for developing efficient AI models and solving complex problems. I highly recommend Apna College's courses, particularly their DSA course, which is made easy to understand and engagingly taught by Shradha Khapra. 4) Familiarity with Machine Learning: AI encompasses various subfields, with machine learning being one of the most prominent. Understanding different machine learning algorithms, such as supervised, unsupervised, and reinforcement learning, is vital. 5) Hands-on Experience 👩💻 : Practical experience is invaluable. Work on projects, participate in hackathons and contribute to open-source projects to build a solid portfolio. Start exploring Kaggle datasets and reviewing their code. Collaborating on Kaggle is one of the easiest ways to begin your coding journey in AI with Python, and Google Colab is particularly user-friendly for beginners. "I believe these insights will provide the answers learners are looking for and help them confidently embark on their AI journey." 😊 #AI #Machinelearning #CareersinAI #Python #Kaggle #Colab #Learners #apnacollege

🌟 Education Recommendation System Using ML ❤️ I’m thrilled to share my Education Recommendation System Using ML. Introduction: The Education Recommendation System is a machine learning-based project designed to assist students in identifying potential career paths based on their academic performance, extracurricular involvement, and other relevant factors. This system leverages a diverse dataset containing student attributes such as academic scores, gender, extracurricular activities, part-time job status, self-study hours, and more to predict career aspirations with associated probabilities. Objectives: The main objective of this project is to provide personalized career recommendations to students. By analyzing each student's unique data, the model predicts the most suitable career choices, which include options like Software Engineer, Doctor, Artist, Teacher, Scientist, Business Owner, and more. This system aims to aid students in making informed career decisions that align with their skills and interests, ultimately fostering better academic and professional outcomes. ↪ 𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: 𝟭. 𝗗𝗮𝘁𝗮 𝗣𝗿𝗲𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: Cleaned and normalized a diverse dataset for optimal input quality. 𝟮. 𝗘𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗼𝗿𝘆 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 (𝗘𝗗𝗔): Leveraged Pandas and Seaborn to visualize patterns and inform feature selection. 𝟯. 𝗠𝗼𝗱𝗲𝗹 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝗼𝗻: Implemented classification algorithms like Random Forest Classifier. 𝟰. 𝗛𝘆𝗽𝗲𝗿𝗽𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿 𝗧𝘂𝗻𝗶𝗻𝗴: Used Grid Search to optimize model performance. 𝟱. 𝗠𝗼𝗱𝗲𝗹 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻: Applied metrics like Confusion Matrix and Classification Report to ensure accuracy and reliability. 🔗 Explore the Code on 𝗚𝗶𝘁𝗛𝘂𝗯: https://lnkd.in/dctibz-3 Let’s connect to explore more insights and collaborative opportunities in the world of data and technology." #EducationRecommedationSystem #MachineLearning #RandomForestClassifier #Python #Pandas #Numpy #Seaborn #Matplotlib #DeepLearning

MIT University offers 11 FREE online courses: Expand your knowledge in Data Science, Computer Science, Business, and More! Follow me Endrit Restelica to stay up to date with tech. 1. Introduction to Computer Science and Programming Using Python - An introduction to computer science as a tool to solve real-world analytical problems using Python 3.5. https://lnkd.in/eNFS_uih 2. Understanding the World Through Data - Become a data explorer – learn how to leverage data and basic machine learning algorithms to understand the world. https://lnkd.in/dpS54npR 3. Fundamentals of Statistics - Develop a deep understanding of the principles that underpin statistical inference: estimation, hypothesis testing and prediction. https://lnkd.in/dcMB_BJN 4. Machine Learning with Python: from Linear Models to Deep Learning An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. https://lnkd.in/dyAk3Z_N. 5. Probability - The Science of Uncertainty and Data Build foundational knowledge of data science with this introduction to probabilistic models, including random processes and the basic elements of statistical inference. https://lnkd.in/d8mwMG6c 6. Supply Chain Analytics - Master and apply the core methodologies used in supply chain analysis and modeling, including statistics, regression, optimization and probability. 7. Becoming an Entrepreneur - Learn the business skills and startup mindset needed to embark on your entrepreneurial path from the premier program for aspiring entrepreneurs, MIT Launch. https://lnkd.in/dK-GSwjT 8. Computational Thinking for Modeling and Simulation - Develop the thought processes involved in formulating a problem so a computer can effectively carry out the solution. In particular, this course emphasizes use of computers for modeling physical systems and predicting their behavior. https://lnkd.in/d8ES6t_f 9. Fundamentals of Manufacturing Processes - Study the processes used to manufacture products ranging from toys to smartphones, and learn fundamental principles and practical considerations that enable production at scale. https://lnkd.in/djjgjyhn 10. Foundations of Modern Finance I - A mathematically rigorous framework to understand financial markets delivered with data-driven insights from MIT professors. https://lnkd.in/dKsh4H7t 11. Introduction to Biology - The Secret of Life - Explore the secret of life through the basics of biochemistry, genetics, molecular biology, recombinant DNA, genomics and rational medicine. https://lnkd.in/d2jxqaah These fields are constantly evolving, and having the right skills can give you a significant edge. Whether you're a recent graduate, a seasoned professional, or simply curious about a new field, these courses offer a fantastic opportunity to learn from a world-renowned institution. Add more in the comments.

🎓 Professional Milestone Alert: Machine Learning Mastery Unlocked! 🎓I am thrilled to announce that I have completed the Machine Learning with Python: A Practical Introduction certification course, a journey that has been both challenging and incredibly rewarding. This course, sponsored by IBM and facilitated by the renowned edX platform, has been a game-changer for my professional development. 🐍 Diving deep into Python programming, I’ve gained hands-on experience with various machine learning algorithms, from simple linear regression to complex neural networks. The curriculum was meticulously crafted, blending theoretical knowledge with practical exercises that truly honed my analytical skills. 🔬 The course covered a spectrum of topics, including data visualization, statistical analysis, predictive modeling, and machine learning pipelines. Each module was a stepping stone that led me to a comprehensive understanding of how machine learning can be applied to solve real-world problems. 💡 One of the highlights of this course was the capstone project, where I applied IBM’s Watson AI to create a predictive model that could have significant implications in the industry. The project not only tested my technical skills but also my ability to think critically and innovate. 🤝 I want to extend my heartfelt gratitude to the instructors and my peers who have been part of this learning odyssey. The collaborative environment and the exchange of ideas have been nothing short of inspiring. 🌟 As I reflect on this accomplishment, I am filled with a sense of pride and a renewed passion for technology. This certification is not just a testament to my dedication but also a key that unlocks new opportunities in the realm of data science and artificial intelligence. 🔗 For anyone considering a foray into machine learning or looking to elevate their Python prowess, I cannot recommend this course enough. It’s a well-structured, immersive experience that truly prepares you for the future of tech. #MachineLearning #DataScience #PythonProgramming #IBM #edX #Certification #CareerGrowth #AI #Technology #Innovation #ContinuousLearning #Techinovate #ML