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Review of Machine Learning Course A-Z 2024: Hands-On Python & R In Data Science3 min read

Review of Machine Learning Course A-Z: Hands-On Python & R in Data Science. This course potentiality brings you to build your successful career in data science.

This is one of the best-selling courses on Udemy, with over 1,025,270 students enrolled and a 4.5/5 star rating with 180.8K+ reviews. With this Best Machine Learning tutorial, Data Science experts will teach you to create Machine Learning Algorithms in Python and R.

Review of Machine Learning Course A-Z: Hands-On Python & R In Data Science

1. What to Learn in this highest-selling Machine Learning Course?

  • Master Machine Learning in Python & R
  • Have a great intuition of many Machine Learning models
  • Make accurate predictions
  • Make a powerful analysis
  • Make robust Machine Learning models
  • Create substantial added value for your business
  • Use Machine Learning for personal purposes
  • Handle specific topics like Reinforcement Learning, NLP, and Deep Learning
  • Handle advanced techniques like Dimensionality Reduction
  • Know which Machine Learning model to choose for each type of problem
  • Build an army of powerful Machine Learning models and know how to combine them to solve any problem

2. What is included in this Machine Learning Certification Course Syllabus?

  • Data Preprocessing
  • Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
  • Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
  • Clustering: K-Means, Hierarchical Clustering
  • Association Rule Learning: Apriori, Eclat
  • Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
  • Natural Language Processing: Bag-of-words model and algorithms for NLP
  • Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
  • Dimensionality Reduction: PCA, LDA, Kernel PCA
  • Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

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3. Who is the target audience?

  • Interested in Machine Learning.
  • Having at least a high school knowledge in math and who knows the basics of Machine Learning.
  • Code free Machine Learning and want to apply it easily to datasets.
  • Fascinated to start a career in Data Science.
  • Wants to become a Data Scientist.
  • Any data analysts who are not satisfied with their job.
  • And who wants to add value to their business by using powerful Machine Learning tools?

4. Who are the Instructors of this Machine Learning Course A-Z?

Kirill Eremenko is a data science coach, lifestyle entrepreneur, aspiring Data Scientist, and forex Systems Expert with a 4.5 average rating and 699.2K+ reviews. He has 2696.4K+ Students and 53 Courses.

Hadelin de Ponteves is an Artificial Intelligence (AI) Entrepreneur with a 4.5 average rating and 343.9K+ reviews. He got more than 1999.2K+ students and 45 courses.

SuperDataScience Team has 710.4K+ reviews and 2735.7K+ students with 4.5 average ratings. They help Data Scientists to Succeed in the Data Science field.

Final Word: Review of Machine Learning Course A-Z 2024

The Machine Learning A-Z has been designed in a way where the instructors share their knowledge and help students learn complex theories, algorithms, and coding libraries simply. I hope this Review of Machine Learning Course A-Z will help you to get started.

Furthermore, the course is packed with practical exercises based on real-life examples. You will also learn hands-on practice building your own models along with the theory.

The course includes both Python and R code templates, which are downloadable and can be used on your projects.

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