The Reviews of 6 Best Data Science Courses On Udemy

Best Data Science Courses On Udemy

Data science is arguably the most desirable course of the twenty-first century.

And with the world now having different problems to solve through the use of data, a scientific algorithm or system must be put in place to extract such insights from existing data.

Normally, there is always too much information for an average individual to be informed about.

Therefore, the work of a data scientist to gather, interpret, and analyze data to conclude comes in.

Truly, data science is a wide subject to cover and learn. Still, you can regardless start learning with the six best data science courses on Udemy listed below.

Reviews of 6 Best Data Science Courses On Udemy 

Do you think Udemy is a learning platform that has a program for you to learn? 

And whether you are interested in high-end machine learning courses or mining programs, it offers quality courses that will help you be well informed of such fields.

In this section, we’ll be discussing courses that will get you started as a beginner, the instructors, and what you will be learning.

Below are our top picks:

1. Machine Learning AZ – Hands-On Python & R In Dat

Machine Learning A Z Python R in Data Science Course Udemy1

This is a very efficient course on Udemy which over the years has had thousands of students go through it. It is a high-end course created by two veteran Data Scientists Hadelin de Ponteves and Kirill Eremenko.

They are amazing tutors who have taught more than a million students each.

This course is of codes up to date, deep learning codes on Tensorflow 2.0, and also specifically designed for anyone who has an interest in machine learning, those who want to start a career in data science, and those who want to level up with heir developed career.

It is divided into 45 sections, 322 lectures, and has a video length of 44h 29m in total.

What You Will Learn:

  • Know Machine Learning on Python & R and know Machine Learning varieties.
  • How to stimulate accurate predictions and powerful analysis.
  • Create strong Machine Learning models and add value to your business.
  • Use Machine Learning while handling topics like Reinforcement Learning, NLP, and Deep Learning.
  • Learn how to handle intelligent strategies like Dimensionality Reduction and be informed of the best model for a different problem.
  • Assemble strong and durable Machine Learning models and know-how to make use of for any problem.

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2. The Data Science Course 2020

Data Science Training Course Data Scientist Bootcamp Udemy2

Data Science 2020 is a good course to get the basics of Machine Learning and Data Science.

Divided into 62 sections and subdivided into 471 lectures, it’s easy to understand terms that make it a very efficient course to opt-in for.

Also, you will be granted access to 154 downloadable resources, 90 articles, lifetime access, and also access on both mobile and TV. A certificate of completion will also be issued upon completion.

This program is designed for data science enthusiasts and those how to wish to take it up as a career.

What You Will Learn: 

  • Know how to pre-process data.
  • Learn the computations behind Machine Learning and begin to code in Python and know how to make use of statistical analysis.
  • Perform logistic and linear regressions in Python and also achieve factor and cluster analysis
  • Learn how to create Machine Learning algorithms in Python, using NumPy, sci-kit-learn, and stats model.
  • Know how to use Deep Learning frameworks like Google’s TensorFlowDevelop while solving tasks with big data.
  • Reveal the power of Deep neural networks.
  • Enhance Machine Learning algorithms by studying various concepts.

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3. Deep Learning A-Z™ – Hands-On Artificial Neural

Deep Learning A Z™ Hands On Artificial Neural Networks Udemy3

Here, you learn more about creating deep learning algorithms in Python from SuperDataScience Team i.e Hadelin de Ponteves and Kirill Eremenko. Both are machine learning and data science professionals.

This program has five language subtitles, i.e German, Italian, Portuguese, Spanish, and English. So the language problem is a bit solved for students of other languages.

It is a very productive course to learn but if you feel you are not getting the much-needed value, there is a 30-day money-back guarantee system. But it does worth the money.

But the course is carefully crafted by two geniuses who have taken hundreds of students on board teaching them about the concepts they need to know to thrive in the data world.

This course is also divided into 26 sections and subdivided into 172 lectures 

What You Will Learn: 

  • The intuition behind Artificial Neural Networks and practice.
  • The intuition behind Convolutional Neural Networks and practice.
  • The intuition behind Recurrent Neural Networks and practice.
  • The intuition behind Self-Organizing Maps and practice.
  • The intuition behind Boltzmann Machines and practice.
  • The intuition behind AutoEncoders and practice.

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4. (Logistic Regression in Python) Deep Learning

Deep Learning Prerequisites Logistic Regression in Python Udemy4

This is a course with a guide into neural networks and deep learning. And apart from teaching you how sone basic technique function in machine learning, it also provides examples for better understanding.

This course is basically for students who want to build a career in machine learning, people who understand some concepts but want to relate it with AI, and adult learners who also want to learn more.

What You Will Learn:

  • How top code logistic regression from scratch in Python
  • Learn how logistic regression works in Data Science 
  • Develop the mistake and redo rule for logistic regression
  • Learn more about Logistic Regression working as an analogy for the biological neuron
  • Solve real-world problems using logistic regression 
  • Know why regularization is made use of in Machine Learning.

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5. Data Science and Machine Learning Bootcamp

Learn Python for Data Science Structures Algorithms Interviews Udemy5

Created by Jose Portilla, this course specifies more on how to use Pandas, Seaborn, Plotly, Tensorflow, NumPy, and a whole lot of others.

The language barrier here has also been lifted as it has six language subtitles plus English. And It has 27 sections for every to take part in and 165 lectures to attend and learn.

However, it is a program of high quality and is only meant for people with at least some level of programming experience.

What You Will Learn:

  • Make use of Spark for Data Analysis.
  • Execute Machine Learning Algorithms and know more about using NumPy for numerical data.
  • Use Pandas for Data Analysis and know more about how to use Matplotlib for Python Plotting.
  • Use Seaborn for statistical plots, Plotly for dynamic visuals, and SciKit-Learn for Machine Learning jobs.
  • Know what K-Means Clustering, Logistic Regression, Linear Regression, Random Forest, and Decision Trees mean.
  • Also, learn more about Natural Language Processing and Spam Filters, Neural Networks, and also support Vector Machines.

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6. R Programming A-Z™

R Programming A Z R For Data Science Course Exercises Udemy6

Learn programming in R and R studio choosing the available ten language subtitles of your choice.

This one comes with lots of ratings and reviews so you taking this course can not be a waste of time.

According to a reviewer on Udemy, he said, “I started the course, left it for a while to work with R, and started again. I find it extremely useful, learning many things yet. 100% recommended.”

What You Will Learn:

  • Learn how to close in R at a very reasonable level and how to make use of R Studio.
  • Learn the core concepts of creating vectors in R, variables, and programming.
  • Know more about integer, double, and other types and also creating a while() loop and a for()loop in R.
  • Know more building, learning, and using matrices, matrix() function, learn rbind() and bind() in R.
  • Know more about installing packages in R and customizing R Studio to your taste.
  • Know the laws of large numbers and normal distribution.
  • Try working with statistical data, financial data, and sports data in R.

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Here the six best data science courses on Udemy, we hope you’ve found value in reading this.

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Written by Wayne K

Wayne K is an educator, freelance content writer that has worked with more than 3 educations blogs. He believes that students, parents needed access to credible information, and he uses the internet to share them.

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