Top 10 Data Science courses

 The data scientist is needed in all areas. They work to extract valuable insights from the clutter of data. Additionally, 80% of helpful information translates into increased corporate reputation and reward, making data scientists earn more than IT staff. Required skills include DBMSs such as MongoDB and MySQL, multidimensional computing, conceptualization and application of probabilities and statistics, and familiarity with common programming languages ​​such as Python or R.

Here are the best free Data Science courses on the Alison platform:

1-Introduction to Data Science

Learn how to extract information from data using data science methods, with this introduction to data science course.

This free online Introduction to Data Science course from Alison will teach you the basics of data science. You will look into data science processes, receive an introduction to machine learning, and learn about data models for structuring data. You will also be shown how to gain knowledge and insights from data that is both structured and unstructured as well as learn to use scientific methods, processes, algorithms, and data science systems.

COURSE PUBLISHERChannel 9

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What You Will Learn In This Free Course

• -Describe what data science is used for
• -List the stages in the data science process
• -Explain what machine learning is and the parts that make it up
• -Discuss the use of regression and the different types of regression
• -Identify the different types of -classification algorithms available for you to use
• -Describe how the two most popular clustering algorithms work
• -Discuss why you would use Azure ML for your data science projects

  

Introduction to Data Science

2-Math for Data Science

Learn the math required for data science and analytics and gain an advantage in business in this free online course.

If your goal is to be a data scientist, analyst or engineer, then some level of mathematical ability is an absolute must. This course covers fundamental linear algebra, probability, and statistics relevant to applying math in data science and the real world.

COURSE PUBLISHERErmin Dedic

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What You Will Learn In This Free Course

• -Discuss the different forms of a linear equation
• -Arrange a system of linear equations into augmented matrix form
• -Solve a system of linear equations using REF or R-REF
• -Define the idea of a vector space and name the two vector spaces introduced during the course
• -Explain how linear independence and span are related
• -Compute a least-squares solution via pseudoinverse
• -Recall the three elements of a probability model
• -Distinguish between a PMF and PDF
• -Compare covariance and variance
• -Contrast the law of large numbers and the central limit theorem
• -Describe the steps involved in computing a joint PDF
• -Indicate how to find the mean squared error using the Bayesian estimator

Math for Data Science

3-Data Science Masterclass for Beginners

Discover if data science is the right path for you by learning about its methodology and more in this free course.

Have you ever wondered how businesses use the vast amounts of data they collect and store? This course will introduce you to some of the skills and tools necessary to work with the most valuable resource of today: data. Various topics are covered, including programming languages, data science methodology and collaboration. Take the first steps in getting involved in the vital task of helping organizations make sense of their information.

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What You Will Learn In This Free Course

• -Define data science
• -Identify the three primary analyses in data mining that focus on extracting patterns
• -Differentiate between machine learning and deep learning
• -Describe the main factors to consider when choosing a programming language to learn
• -Explain each step of data science methodology briefly
• -Indicate the role of entities and intents in chatbot development
• -Outline the purpose and usage of GitHub for online collaboration

Data Science Masterclass for Beginners

4-Advanced Diploma in Data Science with R

In this free online course, learn about the important concepts and essential factors involved in data science with R.

Discover the fundamental aspects of how data science helps businesses make objective and influential decisions in this free online data science with R course. Master the real-world applications of all the data various business sectors accumulate and use it for your clients or employers. You will also gain practical experience on how to discover patterns from raw data and the many career opportunities available in the field of data science.

COURSE PUBLISHERJuan Galvan

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What You Will Learn In This Free Course

• Outline the data science life-cycle stages
• Discuss the concept of data manipulation in R
• Identify the most important operator for data manipulation in R
• Explain the way missing values are represented in R
• Define the concept of data visualization
• Describe the components included in R packages
• Evaluate the two parts of an R Shiny app
• Differentiate between relational and logical operators
• List the examples of one-dimensional data types in R

Advanced Diploma in Data Science with R

5-R Programming for Data Science

This free online R course teaches you the basics of R Programming and how to use it in your data science career.

Learn the various methods and functions of the R programming language in this free online course and the role it can play in the field of data science. You will learn the fundamentals of data science, key topics on R such as data types and structures, functions and methods, packages, getting and cleaning data, plotting data, and data manipulation as well as a practical real-world task where you will get to apply your learning.

COURSE PUBLISHERMohammed Barakat

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What You Will Learn In This Free Course

• Describe Data Science and Big Data
• Explain the Data Science process and tools
• Recognize the main environment and files of RStudio
• Distinguish between different data types in R
• Solve data problems using vectors, matrices, factors, data frames, and lists in R
• Classify controlled-flow data problems using Operators, Conditional Statements, and Loops
• Recognize base R functions and user-defined functions in R
• Analyze data using base mathematical functions, R Packages, and Apply function family
• Translate data using Regular Expressions and Dates & Time functions
• Select and cleanse external data in R
• Label data in R
• Evaluate datasets in R using dplyr package

6-Diploma in Using Python for Data Science

Learn how to use your basic Python knowledge and turn it into a career in data science with this free online course.

Do you have a sound knowledge of Python and would like to start a promising career in data science? With this free online data science certification, you will learn how to apply Python concepts and compound data structures to data science through many different techniques. The content includes understanding numerical Python data analysis, statistics and probability, along with much more to set you on a path of data science success.

COURSE PUBLISHERJuan Galvan

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What You Will Learn In This Free Course

• Define data science
• Discuss machine learning
• Compare data science to machine learning
• List the various applications of machine learning
• Discuss Python programming
• Contrast Jupyter notebook and Google Colab
• Explain Python conditional statements
• Outline hypothesis testing
• Discuss Pandas data analysis
• Explain how to extract a subset from a DataFrame
• Define data visualization
• Categorize data visualization

7-Data Science - Working with Data - Revised

Learn how to prepare and analyze data using different software and programming languages in this free online course.

Any scientific career requires the ability to work with and prepare data. This data science course shows you how to acquire the information you need for a project and how to recognize the usefulness of different data sets. We examine Python and ‘R’ programming languages in Azure Machine Learning (Azure ML) and take you through the lifecycle of data and machine learning. We blend research methodology and programming to teach you data science.

COURSE PUBLISHERChannel 9

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What You Will Learn In This Free Course

• Describe the flow of data in an Azure ML experiment
• Compare R and Python
• Determine which programming language suits you better: R or Python
• Install both R and Python in your Azure ML environment
• Discuss data preparation (or ‘data munging’)
• Define ‘quantization’ and explain your variables 
• Break down how to deal with missing values in data sets
• Explain why you should scale your variables

Data Science - Working with Data - Revised

8-Data Science - Visualizing Data and Exploring Models

Learn about data science techniques, applying visualizations to display data, feature engineering methods, and more!

This free online Data Visualization course teaches you about visualizing data and exploring models. Data visualization is a highly useful way to explore data and can help you determine relationships between columns. With this course, you will learn how to apply visualizations to display your data and about feature engineering and constructing machine learning models. You will learn how to evaluate your model in Azure ML, R, and Python, and more!

COURSE PUBLISHERChannel 9

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What You Will Learn In This Free Course

• Discuss the importance of data exploration
• Recognize what you use for data visualizations in R
• Recognize what you use for data visualizations in Python
• Identify the different types of plots or charts you can use to visualize your data
• Discuss the process of feature engineering
• Identify features and methods available in R for creating Machine learning models
• Identify features and methods available in Python for creating Machine learning models
• Outline the process and options for evaluating your machine learning model

Data Science - Visualizing Data and Exploring Models

9-Python for Data Science: From the Basics to Advanced

This data science course teaches you the basics of Python programming as well as the NumPy and Pandas libraries.

Python is one of the best and fastest-growing programming languages used in data analysis worldwide. This free online course shows you how to apply the fundamental programming concepts of Python such as looping, variables, data types and data structures to data science. It also explores the NumPy and Pandas libraries that will help you further manipulate, analyze and visualize data in Python.

COURSE PUBLISHERErmin Dedic

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What You Will Learn In This Free Course

• Identify the basic data types in Python
• Use the arithmetic, logic, assignment and comparison operators
• Discuss the 'for loop' and 'while loop' structures
• Create and apply functions to perform basic arithmetic operations
• Summarise the nested data and iteration concept in Python
• Create a NumPy array
• Describe NumPy indexing and slicing
• Select data from a data set using both the index-based and label-based methods in Pandas

Python for Data Science: From the Basics to Advanced

10-Data Science - Regression and Clustering Models

Learn how to create regression models, data classification models, and cluster models in Azure ML, R and Python.

This free online data science course will teach you about Regression and Clustering Models. You will look into what regression modelling and classification modelling are, look at their similarity, and learn how each of these models can be created in Azure ML, R, and Python. This course will also discuss the metrics for evaluating a classification model's performance. You will also examine unsupervised learning models, and more!

COURSE PUBLISHERChannel 9

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What You Will Learn In This Free Course

• Discuss the process of regression modelling and how to improve the model
• Identify how to refine a regression model with R
• Identify how to refine a regression model with Python
• Discuss the process of classification modelling and how to improve the model
• Recognise the metrics for evaluating a classification models performance
• Outline how to create a support vector machine model and a decision forest model
• Discuss the process of creating unsupervised learning models
• Recognise how to create hierarchical and k-means clustering models in R
• Recognise how to create hierarchical and k-means clustering models in Python

                 Data Science - Regression and Clustering Models

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