Hey there, friends! So, you’ve been hearing loads about machine learning and you’re kind of curious (and who wouldn’t be!). I mean, this stuff isn’t just a buzzword anymore, it’s become an essential skill set for those in various fields such as tech, marketing, and finance. You want to keep up with the Joneses, but the question remains: where do you even begin to learn? Well, lucky for us, the world wide web offers an incredible array of machine learning resources to dive right into. Online courses? Check! Best part? Many of them are accessible right from the comfort of your own home.
In today’s blog post, we’re going to explore some top-notch machine learning online courses that’ll get you started on this exciting journey. We’ve made sure to gather courses for various skill levels — from beginner to pro — so you’ll find the perfect fit, regardless of your background. Ready to level up your skills and ride the wave of the future in technology? Awesome! Let’s dive in!
Machine Learning Courses – Table of Contents
- Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023]
- Complete Machine Learning & Data Science Bootcamp 2023
- Python for Data Science and Machine Learning Bootcamp
- The Data Science Course: Complete Data Science Bootcamp
- Mathematical Foundations of Machine Learning
- Machine Learning, Data Science and Deep Learning with Python
- The Complete Machine Learning Course with Python
- The Complete Visual Guide to Machine Learning & Data Science
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Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023]
![Course Preview Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus [2023]](https://coursedelta.s3.us-central-1.wasabisys.com/course-img/05312314333403_image..png)
Platform:
Udemy
Rating:
4.6 out of 5
Ready to dive into the world of Machine Learning? This course, designed by a Data Scientist and a Machine Learning expert, makes it easy for you to learn complex theory, algorithms, and coding libraries. Trusted by over 900,000 students worldwide, the course takes you step-by-step through various aspects of Machine Learning, ensuring you develop new skills and deepen your understanding of this sub-field of Data Science.
The course is structured into ten parts, covering topics like Data Preprocessing, Regression, Classification, Clustering, Association Rule Learning, Reinforcement Learning, Natural Language Processing, Deep Learning, Dimensionality Reduction, and Model Selection & Boosting. You can complete the course by working through either the Python or R tutorials, or both—choose the programming language that best fits your career needs. Practical exercises based on real-life case studies will give you hands-on experience in building your own models. Plus, the course includes downloadable Python and R code templates to use in your projects. So, whether you’re looking to acquire new skills or enhance your current ones, this course offers the ultimate learning experience.
Skills you’ll learn in this course:
- Master various regression techniques, including linear, multiple linear, and polynomial regression.
- Gain proficiency in classification methods such as logistic regression, K-NN, SVM, and decision tree classification.
- Acquire skills in clustering algorithms like K-Means and hierarchical clustering.
- Learn association rule learning techniques, such as Apriori and Eclat.
- Understand reinforcement learning concepts – Upper Confidence Bound and Thompson Sampling.
- Develop natural language processing skills using the bag-of-words model and NLP algorithms.
- Dive into deep learning and become familiar with artificial neural networks and convolutional neural networks.
- Master dimensionality reduction methods, including PCA, LDA, and Kernel PCA, and learn model selection and boosting techniques.
Complete Machine Learning & Data Science Bootcamp 2023
Platform:
Udemy
Rating:
4.6 out of 5
Unlock the secrets of data science and machine learning with this comprehensive and up-to-date course, taught by industry experts who have experience in Silicon Valley, Toronto, and other major tech hubs. With over 900,000 engineers already enjoying the benefits of this course, you’ll join a thriving community dedicated to learning and mastering the most current trends and skills in data science. This course is designed for both beginners and experienced programmers, offering separate tracks to cater to different levels of expertise.
Throughout this interactive and project-based course, you’ll gain access to a variety of resources such as workbooks, templates, and code samples, which will be crucial in developing your skills and building your portfolio. The course covers multiple aspects of data science and machine learning, from the basics like Python, TensorFlow 2.0, and model evaluation to more advanced topics like neural networks, deep learning, and transfer learning. By the end of the course, you’ll be ready to tackle real-world projects such as Heart Disease Detection and Dog Breed Image Classifier, demonstrating your newfound expertise as a data scientist and machine learning engineer. So, don’t hesitate – click “Enroll Now” and embark on a journey to transform your career in data science and machine learning.
Skills you’ll learn in this course:
- Data Exploration and Visualizations
- Neural Networks and Deep Learning
- Model Evaluation and Analysis
- Python 3 and associated libraries (Numpy, Scikit-Learn, TensorFlow 2.0)
- Data Science and Machine Learning Projects and Workflows
- Transfer Learning
- Image recognition and classification
- Supervised Learning: Classification, Regression, and Time Series
Python for Data Science and Machine Learning Bootcamp
Platform:
Udemy
Rating:
4.6 out of 5
Are you eager to dive into the world of data science? Look no further, as this comprehensive online course is perfect for those who want to harness the power of Python to analyze data, create stunning visualizations, and utilize machine learning algorithms. Whether you’re a beginner with programming experience or an experienced developer looking to transition into data science, this course has got you covered.
Comparable to costly Data Science bootcamps, this course offers over 100 HD video lectures and detailed code notebooks for each lecture at a fraction of the price. You’ll learn programming with Python, amazing data visualizations with matplotlib, seaborn, and plotly, and machine learning techniques using SciKit Learn. Topics include linear regression, K nearest neighbors, K means clustering, decision trees, random forests, natural language processing, neural nets, and so much more. Enroll now and take the first step towards an exciting and rewarding career in data science!
Skills you’ll learn in this course:
- Programming with Python
- Data analysis using NumPy and pandas Data Frames
- Web scraping with Python
- Connecting Python to SQL databases
- Creating data visualizations with matplotlib, seaborn, and plotly
- Implementing Machine Learning algorithms with SciKit Learn
- Natural Language Processing
- Neural Nets and Deep Learning
The Data Science Course: Complete Data Science Bootcamp
Platform:
Udemy
Rating:
4.6 out of 5
Data science is a booming field with a high demand for skilled professionals. However, acquiring the necessary skills to enter this profession has been a challenge, with limited resources and fragmented online courses. To address this issue, The Data Science Course 2023 offers a comprehensive, structured, and cost-effective training program that covers all the vital topics needed to become a successful data scientist.
The course covers subjects such as data science basics, mathematics, statistics, Python programming, Tableau for data visualization, advanced statistics, and machine and deep learning using TensorFlow. This step-by-step approach ensures that learners acquire the right skills in the right order, providing a solid foundation to excel in the field of data science. By the end of the course, students will have all the knowledge they need to get hired as a data scientist, along with a certificate of completion, active Q&A support, and access to a community of data science learners. Don’t miss the opportunity – join The Data Science Course 2023 today and become a data scientist from scratch!
Skills you’ll learn in this course:
- Understanding of the data science field and the types of analysis carried out
- Mathematics (specifically calculus and linear algebra)
- Statistics and scientific thinking
- Python programming
- Data visualization with Tableau
- Advanced statistical techniques (regressions, clustering, factor analysis)
- Machine Learning
- Deep Learning with TensorFlow
Mathematical Foundations of Machine Learning
Platform:
Udemy
Rating:
4.6 out of 5
If you’re looking to become an exceptional data scientist, getting a strong grasp on mathematics is crucial. In Dr. Jon Krohn’s online course, you’ll dive into the mathematics that lies at the core of machine learning algorithms and data science models. So, not only will you understand the how-tos, but you’ll also uncover the underlying magic of libraries like Scikit-learn and Keras.
The course covers everything from linear algebra data structures and tensor operations to derivatives, differentiation, and integral calculus. Each section offers hands-on assignments, Python code demos, and practical exercises to help you hone your math skills. Plus, enrollment includes future access to bonus content covering probability, statistics, data structures, algorithms, and optimization. Are you ready to elevate your data science game? Join Dr. Jon Krohn’s Mathematical Foundations of Machine Learning course and see where it takes you!
Skills you’ll learn in this course:
- Mastery of linear algebra data structures
- Proficiency in tensor operations
- Understanding of matrix properties
- Knowledge of eigenvectors and eigenvalues
- Ability to perform matrix operations for machine learning
- Familiarity with limits, derivatives, and differentiation
- Proficiency in automatic differentiation
- Skills in partial-derivative and integral calculus
Machine Learning, Data Science and Deep Learning with Python
Platform:
Udemy
Rating:
4.6 out of 5
Discover the fascinating world of Machine Learning and Artificial Intelligence with this comprehensive online course that offers over 100 lectures and 15 hours of video content. With hands-on Python code examples and an easy-to-understand approach, you’ll learn the techniques used by real data scientists and machine learning practitioners, preparing you to step into a hot career path with an average salary of $120,000. You don’t need to be a math whiz to understand this course; it’s designed for anyone with some programming or scripting experience looking to switch career tracks, enter the tech industry or expand their knowledge.
The course covers a wide range of topics from Deep Learning and Neural Networks to Data Visualization, Sentiment Analysis, and Image Recognition. Plus, it dives into advanced techniques such as Generative Adversarial Networks (GAN’s), Variational Auto-Encoders (VAE’s), Transfer Learning, and Ensemble Learning. To top it off, you’ll also learn about machine learning with Apache Spark and how machine learning can be applied to big data analyzed on a computing cluster. Whether you’ve got experience with Python or you’re just starting out, this course is designed to help you hit the ground running, regardless of your operating system. So why wait? Enroll now and start your journey into the exciting field of Machine Learning and AI today!
Skills you’ll learn in this course:
- Deep Learning / Neural Networks with TensorFlow and Keras
- Data Visualization in Python with MatPlotLib and Seaborn
- Sentiment Analysis
- Image Recognition and Classification
- Regression Analysis
- K-Means Clustering
- Decision Trees and Random Forests
- Feature Engineering
The Complete Machine Learning Course with Python
Platform:
Udemy
Rating:
4.5 out of 5
The Complete Machine Learning Course in Python has been fully updated for November 2019, offering fresh and improved content to help you master Machine Learning. With brand new sections on Foundations of Deep Learning and Computer Vision, the course also includes updates on Google Colab, Deep Learning, NLP, binary and multi-class classifications, and much more. Prepare to be equipped with the most up-to-date information and practices in the field.
On top of gaining a comprehensive understanding of machine learning, you’ll also build a portfolio of 12 Machine Learning projects that can help you land a high-paying job or solve real-world problems in various aspects of your life. Taught by Anthony NG, a Senior Lecturer from Singapore, this course features over 18 hours of content and boasts a strong rating. Through the hands-on learning approach, you’ll train machine learning algorithms to tackle tasks like classifying flowers, predicting house prices, identifying handwritings or digits, and even detecting cancer cells. With no prior Machine Learning knowledge required, you’ll develop everything from complete machine learning toolsets to the effective use of Matplotlib and Seaborn for visual communication.
Skills you’ll learn in this course:
- Master the foundations of deep learning and understand the differences between classical programming and machine learning.
- Acquire skills in computer vision using convolutional neural networks.
- Gain a complete machine learning toolset to tackle real-world problems.
- Understand and apply various regression, classification, and other machine learning algorithms.
- Develop skills in using Jupyter (IPython) notebook, Spyder, and other IDEs.
- Effectively communicate and visualize data using Matplotlib and Seaborn.
- Engineer new features to improve algorithm predictions.
- Utilize train/test, K-fold, and Stratified K-fold cross-validation techniques to select the correct model and predict model performance with unseen data.
The Complete Visual Guide to Machine Learning & Data Science
Platform:
Udemy
Rating:
4.8 out of 5
This beginner-friendly machine learning and data science course is designed to build confidence through guided, step-by-step demonstrations, teaching foundational skills from the ground up. Through user-friendly, Excel-based models, you’ll learn topics like linear and logistic regression, decision trees, KNN, naïve bayes, hierarchical clustering, and sentiment analysis—all without writing a single line of code. The course combines 4 best-selling courses from Maven Analytics into a single masterclass, enabling you to explore real-world scenarios that simulate actual data science and business intelligence cases.
The course offers immediate, lifetime access to 9+ hours of on-demand video, a 350+ page Machine Learning Foundations ebook, downloadable Excel project files, and expert Q&A forums. Throughout the course, you’ll work on real-world projects such as building a recommendation engine for Spotify, analyzing customer purchase behavior, forecasting sales for a new product launch, and more. If you’re an analyst or aspiring data professional looking to build a solid foundation for a successful career in machine learning or data science, this course is the ideal starting point. Happy learning!
Skills you’ll learn in this course:
- Understanding machine learning techniques and workflows
- Conducting univariate and multivariate profiling
- Applying classification models (e.g., KNN, Naïve Bayes, Decision Trees)
- Performing regression and time-series forecasting
- Evaluating model performance and diagnostics
- Exploring unsupervised learning techniques (e.g., clustering, association mining)
- Implementing outlier detection and dimensionality reduction methods
- Analyzing and visualizing real-world datasets with Excel-based models
And there you have it! We’ve covered some of the best machine learning online courses available to help you jumpstart your learning journey. Whether you’re a beginner just dipping your toes into the fascinating world of AI or an experienced professional looking to hone your skills further, these courses have something to offer everyone. Keep in mind that learning never stops, and staying up-to-date with industry trends, best practices, and emerging tools is a crucial part of staying ahead of the game.
As you power through these courses, don’t forget the importance of hands-on experience and collaboration with like-minded peers. Join online communities, attend local meetups, and always be open to constructive feedback on your projects. A strong foundation in machine learning combined with practical experience and ongoing networking will help pave the way for a successful career in this field. Happy learning, and don’t be afraid to let your curiosity lead the way!