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Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

  • 1.  Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Tue July 28, 2020 02:23 PM
    Edited by Miguel Maldonado Wed July 29, 2020 05:39 PM
    IBM just announced the Introduction to Machine Learning specialization on Coursera. As the lead curriculum developer for this set of  courses, I would like to share with you some of the highlights and how I think you can benefit the most from signing up today.
     
    The IBM Introduction to Machine Learning specialization will help you realize the potential of machine learning in a business setting. You will be able to realize the potential of machine learning and artificial intelligence in different business scenarios. You will also be able to identify when to use machine learning to explain certain behaviors and when to use it to predict future outcomes. Finally, you will learn how to evaluate your machine learning models and to incorporate best practices.
     
    The specialization has 4 courses:
     
    Exploratory Data Analysis for Machine Learning
    This course helps you make the most out of your data by using Exploratory Data Analysis, Feature Engineering, and Feature Transformation. You start with a quick dive into Modern AI and Machine Learning applications. Then you learn tools and techniques that will be very useful throughout the rest of the specialization. Data is the main asset for Machine Learning and AI. You will lean how to get your data in great shape, find insights, and test hypothesis.

    Supervised Learning: Regression
    This course starts your journey in Supervised Learning with Linear Regression, a powerful algorithm from Statistical Learning that will be a solid foundation for more modern algorithms. It also introduces several key concepts like error metrics, data partition, and regularization, which will be important for you to compare the results across different Machine Learning models and select the model that best suits your analysis. These concepts also help you make sure your Machine Learning model generalizes well with new data.

    Supervised Learning: Classification
    This course focuses on techniques that help you either explain past events or predict future events. Professionals like you use these techniques to, for example, predict whether a customer will return to a store, or the likelihood of a student to graduate from a specific course; or to explain the main drivers of past customer engagement, successful online marketing campaigns, and customer retention. Specific Supervised Learning classification techniques that you will learn include Logistic Regression, K-nearest neighbors, Decision Trees, and Ensemble Modeling. You will also learn to deal with data sets with unbalanced classes, in case you are trying to predict rare events.

    Unsupervised Learning
    This course walks you through techniques that help you leverage data that does not have a labeled outcome or event, or even to take a deeper dive into your data after you have performed Supervised Learning analysis on your data. Companies from around the globe use unsupervised learning to quantify the quality of their data, segment their customers, and group similar observations together for further analysis. This course walks you through clustering algorithms like K-Means, Hierarchical Clustering, and DBSCAN, as well as dimension reduction techniques like Principal Component Analysis and Matrix Factorization.
     
    Each course of the specialization has lectures with theoretical framework, code-along demonstrations, and a project that helps you highlight your analytical and Machine Learning skills. On top of submitting your final deliverables for peer review, you are highly encouraged to post them here on the online communities or on an online portfolio.

    If you are looking for a short, comprehensive specialization to brush up on the theory behind Machine Learning, gain hands-on practice in the most common open source frameworks for Machine Learning, and use this opportunity to highlight your Machine Learning skills, sign up today for the IBM Introduction to Machine Learning specialization.




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    Miguel Maldonado

    IBM - Data and AI Learning
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  • 2.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Wed August 05, 2020 03:56 AM
    Hi Miguel, Thank you for sharing. May I know if there is any significant difference between this course and IBM data science professional courses? Since machine learning with python is included in this course and seems all algorithms has been covered. It is appreciated if you explain the differences. Thanks

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    Samira Gholizadeh
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  • 3.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Mon August 24, 2020 08:43 AM
    Hi Samira, Think of this specialization as the next level after the Data Science courses. It is a deep dive into machine learning.... all the way from preparing data for modeling, building different models from scratch, and evaluating models to determine the right model to deploy. It goes deep into supervised, and unsupervised learning.  In the next couple of months, we will be launching 2 other courses focused on deep learning and reinforcement learning + survival analysis and time series techniques.

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    Ana Echeverri
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  • 4.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Mon August 24, 2020 09:21 AM
    Hi Ana 

    Thank you for explanation. Thats great... I will go through the specialization course and I am looking forward to having deep learning and reinforcement learning courses. I hope I receive email from coursera once the course is ready.

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    Samira Gholizadeh
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  • 5.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Mon August 24, 2020 09:32 AM
    Absolutely. By the time you finish the existing 4 courses on the path, the other 2 courses will be live :-)

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    Ana Echeverri
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  • 6.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Mon August 24, 2020 09:43 AM
    Thats amazing. Many thanks :-)

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    Samira Gholizadeh
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  • 7.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Thu August 27, 2020 10:12 AM
    Hi Ava, I wanted to know whether the 2 other courses that will be released in the next few months be part of the same IBM Introduction to Machine Learning specialization or will there be a new specialization released?

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    Raunak Bhutoria
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  • 8.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Thu August 27, 2020 10:29 AM
    The 2 new courses will be put together with the existing 4 in this specialization as a new Machine Learning Professional Certificate.

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    Ana Echeverri
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  • 9.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Thu August 27, 2020 01:58 PM
    It is highly appreciated Ms Ana if you share the links here when they are ready. Thanks

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    Samira Gholizadeh
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  • 10.  RE: Round your Machine Learning skills with IBM Introduction to Machine Learning specialization

    Posted Wed September 23, 2020 01:25 PM

    The last 2 courses of the series just launched:

    -Deep Learning and Reinforcement Learning

    -Specialized Topics: Time Series Analysis and Survival Analysis

    Here is a link to the Professional Certificate: https://www.coursera.org/professional-certificates/ibm-machine-learning

    Let us know what you think!



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    Miguel Maldonado
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