Data Science, Deep Learning, & Machine Learning with Python-Udemy Free (100%)

Data Science, Deep Learning, & Machine Learning with Python

Go hands-on with the neural network, artificial intelligence, and machine learning techniques employers are seeking!
[100% OFF Udemy COUPON] Free Original price: $160 Discount: 100% off

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Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That's just the average! And it's not just about money - it's interesting work too!

If you've got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry - and prepare you for a move into this hot career path. This comprehensive course includes over 80 lectures spanning 12 hours of video, and most topics include hands-on Python code examples you can use for reference and for practice. I’ll draw on my 9 years of experience at Amazon and IMDb to guide you through what matters, and what doesn’t.

Each concept is introduced in plain English, avoiding confusing mathematical notation and jargon. It’s then demonstrated using Python code you can experiment with and build upon, along with notes you can keep for future reference. You won't find academic, deeply mathematical coverage of these algorithms in this course - the focus is on practical understanding and application of them. At the end, you'll be given a final project to apply what you've learned!

The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. We'll cover the machine learning and data mining techniques real employers are looking for, including:

    Deep Learning / Neural Networks (MLP's, CNN's, RNN's)
    Regression analysis
    K-Means Clustering
    Principal Component Analysis
    Train/Test and cross validation
    Bayesian Methods
    Decision Trees and Random Forests
    Multivariate Regression
    Multi-Level Models
    Support Vector Machines
    Reinforcement Learning
    Collaborative Filtering
    K-Nearest Neighbor
    Bias/Variance Tradeoff
    Ensemble Learning
    Term Frequency / Inverse Document Frequency
    Experimental Design and A/B Tests


...and much more! There's also an entire section on machine learning with Apache Spark, which lets you scale up these techniques to "big data" analyzed on a computing cluster. And you'll also get access to this course's Facebook Group, where you can stay in touch with your classmates.

If you're new to Python, don't worry - the course starts with a crash course. If you've done some programming before, you should pick it up quickly. This course shows you how to get set up on Microsoft Windows-based PC's; the sample code will also run on MacOS or Linux desktop systems, but I can't provide OS-specific support for them.

If you’re a programmer looking to switch into an exciting new career track, or a data analyst looking to make the transition into the tech industry – this course will teach you the basic techniques used by real-world industry data scientists. I think you'll enjoy it!