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Complete Data Science BootCamp | Free Udemy Course
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Complete Data Science BootCamp | Free Udemy Course

Free $84.99100% off
Price expires 11 months ago or 428 uses

Learn about Data Science, Machine Learning and Deep Learning and build 5 different projects. | Free Udemy Course

4.69
(41 ratings)
10018 students
Created by:
Last updated 1/2023Course Language EnglishCourse Caption English [Auto]Course Length 07:36:59 to be exact 27419 seconds!Number of Lectures 54
This course includes:
  • 7.5 hours hours of on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion
  • 61 additional resources

Data science is the field that encompasses the various techniques and methods used to extract insights and knowledge from data. Machine learning (ML) and deep learning (DL) are both subsets of data science, and they are often used together to analyze and understand data.In data science, ML algorithms are often used to build predictive models that can make predictions based on historical data. These models can be used for tasks such as classification, regression, and clustering. ML algorithms include linear regression, decision trees, and k-means.DL, on the other hand, is a subset of ML that is based on artificial neural networks with multiple layers, which allows the system to learn and improve through experience. DL is particularly well-suited for tasks such as image recognition, speech recognition, and natural language processing. DL algorithms include convolutional neural networks (CNNs) and recurrent neural networks (RNNs).In a data science project, DL models are often used in combination with other techniques such as feature engineering, data cleaning, and visualization, to extract insights and knowledge from data. For instance, DL models can be used to automatically extract features from images, and then these features can be used in a traditional ML model.In summary, Data science is the field that encompasses various techniques and methods to extract insights and knowledge from data, ML and DL are subsets of data science that are used to analyze and understand data, ML is used to build predictive models and DL is used to model complex patterns and relationships in data. Both ML and DL are often used together in data science projects to extract insights and knowledge from data.IN THIS COURSE YOU WILL LEARN ABOUT :Life Cycle of a Data Science Project.Python libraries like Pandas and Numpy used extensively in Data Science.Matplotlib and Seaborn for Data Visualization.Data Preprocessing steps like Feature Encoding, Feature Scaling etc...Machine Learning Fundamentals and different algorithmsCloud Computing for Machine LearningDeep Learning 5 projects like Diabetes Prediction, Stock Price Prediction etc...ALL THE BEST !!!Who this course is for:People who want to start their Data Science Journey in Python.Someone who is looking for a complete course that covers all important topics of Data Science, Machine Learning and Deep Learning.

Course Content:

Sections are minimized for better readability, click the section title to view the course content

1 Lectures | 06:25
7 Lectures | 59:46
5 Lectures | 26:41
3 Lectures | 25:47
3 Lectures | 28:00
16 Lectures | 02:13:41
9 Lectures | 01:17:50
5 Lectures | 38:22
5 Lectures | 01:00:27
4.69
(41 course ratings)
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If you like to get inspired by great web projects, you should check out Made with Javascript. If you have a project that you wish to share with the world, feel free to submit your project on Made with Javascript Club website.

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