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via Udemy |
Go to Course: https://www.udemy.com/course/machine-learning-using-r/
Certainly! Here's a comprehensive review and recommendation for the Coursera course on Data Science & Machine Learning based on the provided details: --- **Course Review: Data Science & Machine Learning on Coursera** If you're intrigued by the rapidly expanding fields of Data Science and Machine Learning, this Coursera course offers a fantastic starting point. Designed for a broad audience — from complete beginners with no programming experience to experienced developers looking to upskill — this course provides a hands-on, practical approach to mastering key concepts and tools in data science. **What Makes This Course Stand Out?** 1. **Hands-On Learning:** Unlike many theoretical courses, this program emphasizes practical implementation. Students get to learn by doing, with real-time visualizations and experimentation, which enhances understanding and retention. 2. **Comprehensive Curriculum:** Covering essential data structures such as vectors, matrices, data frames, and factors in both R and Python, the course equips learners with foundational programming skills. It also delves into data visualization and critical machine learning models like linear/regression, decision trees, random forests, neural networks, and deep learning. 3. **Focus on Understanding:** The course emphasizes conceptual clarity over rote memorization. Learners see how models work internally, enabling more effective application of techniques in real-world scenarios. 4. **Versatile Content:** Whether you’re interested in leveraging data science for business insights, career advancement, or even automating complex systems like driverless cars, this course is relevant. It demonstrates applications from Netflix recommendations to fraud detection. 5. **Free Resources:** All course materials are free, including software downloads for R and Python, making it accessible regardless of your financial situation. 6. **Flexible Learning:** Suitable for high school students, college students, data analysts, and career changers alike. The course is designed to fit varied backgrounds and goals. **What I Would Like to See Improved** While the course offers a thorough and practical approach, it could benefit from additional industry case studies or project work to further enhance real-world applicability. A certification or portfolio project might be useful for those seeking employment or career transition. **My Recommendation** I highly recommend this course for anyone interested in entering the exciting field of Data Science and Machine Learning. Its beginner-friendly yet comprehensive structure makes it ideal for a wide range of learners. The emphasis on doing rather than just theory ensures you gain practical skills that are immediately applicable. Plus, learning both R and Python equips you with versatile tools used across the industry. **Final Verdict:** If you're motivated to start a rewarding career, increase your job prospects, or simply understand the power of data in the modern world, this course is an excellent investment in your future. Enroll today, and take your first step towards becoming a data scientist! --- Let me know if you'd like a shorter version or a personalized review!
Interested in the field of Data Science & Machine Learning? Then this course is for you!Learn Data Science & Machine Learning by doing! Hands On Experience Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!This course is for those : Anyone interested in Machine Learning.Students who have at least high school knowledge in math and who want to start learning Machine Learning.Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.Any students in college who want to start a career in Data Science.Any data analysts who want to level up in Machine Learning.Any people who are not satisfied with their job and who want to become a Data Scientist.Any people who want to create added value to their business by using powerful Machine Learning tools.What is Data Science ?Data science is used to extract patterns or insights from data to predict future or to understand customer behavior and so on.Data science is a "concept to unify statistics, data analysis and their related methods" in order to "understand and analyze actual phenomena" with dataMining large amounts of structured and unstructured data to identify patterns can help an organization to reduce costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.Some Data Science and machine learning ApplicationsNetflix uses data science & machine learning to mine movie viewing patterns to understand what drives user interest, and uses that to make decisions on which Netflix original series to produce.Companies like Flipkart and Amazon uses data science and machine learning to understand the customer shopping behavior to do better recommendations.Gmail's spam filter uses data science (machine learning algorithm) to process incoming mail and determines if a message is junk or not..Proctor & Gamble utilizes data science (machine learning ) models to more clearly understand future demand, which help plan for production levels more optimally.Why Programming Won't Work in some Cases??Have you ever thought of the scenario where all the cars will be moving without a driver that means something like automated machines say for example automatic washing machine.But there is a difference.1. For automatic washing machine,we can write programs for the washing machine functionality.2. For automated cars without drivers in high traffic.Just imagine ,how complex and dangerous it will be when someone starts coding /programming for such functionalities.For cars to automate we would require something which is called "Machine Learning "COURSE DETAILS AS BELOW :DATA STRUCTURES ,etc. in R & PYTHON as follows:1. Vectors2. Matrices3. Data Frames4. Factors 5. Numerical/Categorical Variables6. List7. How to convert matrix into data framePROGRAMMING IN R &PYTHONDATA VISUALIZATIONIMPLEMENTATION OF MACHINE LEARNING MODELS as follows:1. Linear Regression & Logistic Regression2. Decision Tree3. Random Forest4.Neural Networks5. Deep learning 6. H2o framework7. Cross validation /How to avoid Over fitting8. Dimensionality Reduction Techniques LEARN FROM SCRATCH [HOW TO DO ML IN PYTHON] SEE IN REAL TIME HOW OPTIMIZATION WORKS TO GET A MACHINE LEARNING MODELAll the materials for this data science & machine learning course are FREE. You can download and install R & Python, with simple commands on Windows, Linux, or Mac.This course focuses on "how to build and understand", not just "how to use".It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. THE COURSE IS DESIGNED IN SUCH A WAY WHICH GIVES MORE OF PRACTICAL SENSE FOR MACHINE LEARNING & DATA SCIENCE IN VERY LESS AMOUNT OF TIMESo what are you waiting for ? Enroll in this course and start your future journey!!