Data Analysis Courses For Beginners

Are you seeking the Best Data Science Online Courses?

If that’s the case, this article will put an end to your hunt. In this article, compiled a list of the 15 Best Online Data Science Courses.

These courses will help you improve your data science abilities. So go ahead and study the entire post before deciding on the Best Online Courses for you.

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As you know, there are a variety of courses and books that might assist you in your data science journey.

It can be tough to read novels at times. As a result, a variety of online courses are available. You may study advanced data science skills at your own speed with these courses.

This article will provide you with the 15 Best Online data analysis courses for beginners.

1. IBM Data Science Professional Certificate– Coursera

Provider- IBM

This is one of the most popular and well-received course series. This IBM Professional Certificate is for anyone interested in pursuing a career in Data Science.

There are nine courses in this curriculum. These nine courses will cover open source tools and libraries, methods, Python, databases, SQL, data visualization, data analysis, and machine learning, among other topics.

No prior experience in computer science or programming is required to begin the IBM Professional Certificate Program.

Let’s have a look at the talents you’ll get after completing this course:

Skills Gain:-

Data Science, Machine Learning, Python Programming, Data Analysis, Data Visualization (DataViz), Predictive Modelling, Relational Database Management System (RDBMS), SQL, Cloud Databases, Pandas, Numpy, and Ipython.

Hands-on assignments and built a portfolio of data science projects.

Tools:-

Jupyter/JupyterLab, Zeppelin notebooks, R Studio, Watson Studio

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Projects:-

Random album generator, Predict housing prices, Best classifier model, Battle of neighborhoods.

Courses include–This Specialization Program consists of 9 Courses-

What is Data Science?, Tools for Data Science, Data Science Methodology, Python for Data Science and AI, Databases and SQL for Data Science, Data Analysis with Python, Data Visualization with Python, Machine Learning with Python, Applied Data Science Capstone

You can also sign up for a specific course. You will also receive a shareable certificate after completing a single course. However, finishing the entire curriculum will benefit you.

Coursera will award you a Professional Certificate as an added bonus, IBM will issue you a Digital Badge, You will receive FREE career materials after earning the Professional Certificate.

Who Should Enroll in the Program?

Who is a Data Science newbie with no prior experience?

The person who wants to start a new career or alter their existing one.

2. Become a Data Scientist– Udacity

Udacity is offering a Nano-Degree Program. You will learn how to solve Data Science problems utilizing Python programming, Software Engineering skills, and Data Engineering skills in this Nanodegree program.

The nicest part of the Udacity Data Science Nanodegree is that it is more hands-on than other courses. That is, the Udacity data science Nanodegree is structured in such a way that you must submit a project following each set of classes.

You will work on the following projects as part of this Nanodegree program:

Build Disaster Response Pipelines with Figure Eight

Figure Eight is used to create disaster response pipelines, and IBM is used to create a recommendation engine.

You must select one of these projects for your Data Science Capstone Project, or you may select any other project.

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Dog Breed Classification( Neural Networks), Starbucks( Customer Segmentation), Arvato Financial Services (Likely Supervised Learning), Spark for Big Data (Customer churn with PySpark), Any other project of your choice.

Extra Benefits- You will have the opportunity to collaborate with industry experts on real-world projects.

Experienced reviewers will provide input on your project.

You’ll also have access to a technical mentor.

Who should sign up?

Those who are familiar with the principles below-

Python programming, which includes a number of popular data analysis packages (NumPy, pandas, Matplotlib), SQL programming language, Statistical data (Descriptive and Inferential), Linear Algebra Calculus, and Data wrangling and visualization experience.

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