5.00
(1 Rating)

IBM Introduction to Machine Learning Specialization

Wishlist Share
Share Course
Page Link
Share On Social Media

About Course

IBM Introduction to Machine Learning Specialization – FREE!

Want to unlock the power of machine learning and land a high-paying job? This **free** IBM Introduction to Machine Learning Specialization course from Coursera will equip you with the essential skills needed to succeed in the data science and machine learning fields. Learn from IBM experts and gain a comprehensive understanding of machine learning algorithms and artificial intelligence, including:

  • Understanding machine learning applications in various business scenarios
  • Predicting future outcomes and explaining behaviors
  • Evaluating machine learning models and applying best practices
  • Building a strong portfolio of machine learning projects

Upon completion, you’ll receive a certificate from Coursera and an IBM Badge of Honor, showcasing your skills to potential employers. This course is part of the 6-part IBM Machine Learning Professional Certificate series, offering a complete pathway into a rewarding career in machine learning.

**Enroll in this FREE course today and start your journey towards a successful career in machine learning!**

**This course is available on Theetay.com, a platform offering free access to top-rated courses from leading providers like Udemy, Udacity, Coursera, MasterClass, NearPeer and more. **

Show More

What Will You Learn?

  • Understanding the potential applications of machine learning
  • Acquire technical skills such as SQL, machine learning modeling, supervised and unsupervised learning, regression and classification.
  • Identify opportunities to use machine learning in your organization or profession
  • Communicating the findings of machine learning projects with experts and non-experts

Course Content

01. ibm-exploratory-data-analysis-for-machine-learning
new topic

  • 0057 003_handling-missing-values-and-outliers-using-residuals.mp4
    00:00
  • 0061 001_introduction-to-exploratory-data-analysis-eda.mp4
    00:00
  • 0064 002_eda-with-visualization.mp4
    00:00
  • 0067 003_grouping-data-for-eda.mp4
    00:00
  • 0068 004_optional-download-assets-for-lab-exploratory-data-analysis-lab_01c_LAB_EDA.zip
    00:00
  • 0072 005_optional-solution-eda-notebook-part-1.mp4
    00:00
  • 0075 006_optional-solution-eda-notebook-part-2.mp4
    00:00
  • 0078 007_optional-solution-eda-notebook-part-3.mp4
    00:00
  • 0081 008_optional-solution-eda-notebook-part-4.mp4
    00:00
  • 0084 001_feature-engineering-and-variable-transformation-background.mp4
    00:00
  • 0087 002_variable-transformation.mp4
    00:00
  • 0090 003_feature-encoding.mp4
    00:00
  • 0093 004_feature-scaling.mp4
    00:00
  • 0096 005_common-variable-transformations-in-python.mp4
    00:00
  • 0097 006_optional-download-assets-for-lab-feature-engineering-demo_01d_DEMO_Feature_Engineering.zip
    00:00
  • 0101 007_optional-solution-feature-engineering-lab-part-1.mp4
    00:00
  • 0104 008_optional-solution-feature-engineering-lab-part-2.mp4
    00:00
  • 0107 009_optional-solution-feature-engineering-lab-part-3.mp4
    00:00
  • 0111 001_estimation-and-inference-introduction.mp4
    00:00
  • 0114 002_estimation-and-inference-example.mp4
    00:00
  • 0117 003_estimation-and-inference-parametric-vs-non-parametric.mp4
    00:00
  • 0120 004_estimation-and-inference-commonly-used-distributions.mp4
    00:00
  • 0123 005_frequentist-vs-bayesian-statistics.mp4
    00:00
  • 0126 001_introduction-to-hypothesis.mp4
    00:00
  • 0129 002_hypothesis-testing-example.mp4
    00:00
  • 0132 003_bayesian-interpretation-of-hypothesis-testing-example.mp4
    00:00
  • 0135 004_type-1-vs-type-2-error.mp4
    00:00
  • 0138 005_type-1-vs-type-2-error-examples.mp4
    00:00
  • 0141 006_hypothesis-testing-terminology.mp4
    00:00
  • 0144 007_significance-level-and-p-values.mp4
    00:00
  • 0147 008_significance-level-and-p-values-and-the-f-statistic.mp4
    00:00
  • 0148 009_optional-download-assets-for-lab-hypothesis-testing-demo_01e_DEMO_Hypothesis_Testing.zip
    00:00
  • 0152 010_optional-hypothesis-testing-demo-part-1.mp4
    00:00
  • 0155 011_optional-hypothesis-testing-demo-part-2.mp4
    00:00
  • 0158 012_correlation-vs-causation.mp4
    00:00
  • 0159 001_summary-review_instructions.html
    00:00
  • 0004 002_course-prerequisites_instructions.html
    00:00
  • 0003 001_course-introduction.mp4
    00:00
  • 0010 002_machine-learning-and-deep-learning.mp4
    00:00
  • 0013 003_machine-learning-and-deep-learning-part-1.mp4
    00:00
  • 0016 004_machine-learning-and-deep-learning-part-2.mp4
    00:00
  • 0019 005_history-of-ai.mp4
    00:00
  • 0022 006_history-of-machine-learning-and-deep-learning.mp4
    00:00
  • 0025 001_modern-ai.mp4
    00:00
  • 0028 002_applications.mp4
    00:00
  • 0031 003_machine-learning-workflow.mp4
    00:00
  • 0035 001_retrieving-data-from-csv-and-json-files.mp4
    00:00
  • 0038 002_retrieving-data-from-databases-apis-and-the-cloud.mp4
    00:00
  • 0039 003_optional-download-assets-for-lab-reading-data-in-database-files-part-a_01a_DEMO_Reading_Data.zip
    00:00
  • 0043 004_optional-lab-solution-reading-data-jupyter-notebook-part-a.mp4
    00:00
  • 0044 005_optional-download-assets-for-lab-reading-data-in-jupyter-notebook-part-b_01b_LAB_Reading_Data.zip
    00:00
  • 0048 006_optional-lab-solution-reading-in-database-files-part-b.mp4
    00:00
  • 0051 001_data-cleaning.mp4
    00:00
  • 0054 002_handling-missing-values-and-outliers.mp4
    00:00
  • Section Quiz

02. supervised-machine-learning-regression
new topic

03. supervised-machine-learning-classification
new topic

04. ibm-unsupervised-machine-learning
new topic

Earn a certificate

Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.

selected template

Student Ratings & Reviews

5.0
Total 1 Rating
5
1 Rating
4
0 Rating
3
0 Rating
2
0 Rating
1
0 Rating
FS
1 month ago
It was excellent

Want to receive push notifications for all major on-site activities?

×