Data Science is one of the emerging fields of time. In the last article about data science, I discussed key concepts like who is a data scientist? Key Skills Required for a data scientist.
Now, in this article, we will move forward one step ahead and will cover the courses which are available online for data sciences.
Big data technologies have a greatly simplified day to day work and personal activities. Companies all around the world are seeking data scientists for their projects now.
Check the following courses to become a data scientist and enter the new world of technology:
Coursera in association with John Hopkins University is considered as one of the earliest online learning data science educational institutions.
It offers a paid program but discounts are available as well. It comprises of 10 courses. Students submit a data product for solving real-world problems for completing the program.
It is another course offering from Coursera. The course focuses on business applications. It covers tools and techniques which are used for tackling data challenges. It is a four-week course. In the end, Students have to deploy a data solution in a business environment.
This course is offered by Microsoft. It can be taken as a standalone course through EdX as well. This course needs prerequisites which include introductory knowledge of R and Python.
The course includes chapters of probability and statistics, data exploration visualization, introduction to machine learning with Microsoft Azure. It’s a free course but for certification, $90 are charged.
This course is more oriented towards machine learning which is, of course, one of the hottest subjects of the time.
This course is designed to give a full overview from theory to practical side. It also gives detailed insights into choosing the right algorithms for particular scenarios.
Formerly IBMs portal known as big data university and now rebranded as a cognitive class has been offering learning data science courses for along.
This program covers chapters like programming in R, data science 101, hands-on applications and open source tools. Approximate course length is 20 hours. However, prior knowledge may affect the length of the course.
It is not affiliated with any other university. Offers a lot of free resource materials along with advanced courses with premium packages.
Three paths are offered by Dataquest which are a data scientist, data engineer and data analyst. It has endorsements from reputable businesses like Amazon, Spotify, and Uber.
KDNuggets is a very popular website among data scientists. It has data mining syllabus. It consists of modules like regression, clustering, decision trees.
I highly recommend following KDNuggets regularly for getting yourself up to date with data science concepts.
This course contains open source materials and resources available entirely for free. It includes subjects of study on natural language processing of Twitter API by Python, SQL, Hadoop MapReduce, NoSQL databases and visualization.
Moreover, the core concepts of algebra and statistics which are necessary for building data science base is also included in this course.
Analytics Edge is good for getting started with R. It gives a brief intro to R. It gives hands-on experience with statistical modeling techniques.
This course is good if you wanna learn practical analytics methods which don’t require a math background. Total course length is 11 weeks.
This course comprises R, machine learning, statistics, and SAS programming. This course is ideal for those who wanna enter data science field but don’t have a programming background.
You should score at least 80 percent to get certified. You will have to complete at least 1 industry level project. This course requires basic knowledge of machine learning and statistics.
It’s a nano degree provided by Udacity and AT & T. The course continues from duration 6 to 12 months. Subjects include python, R, MongoDB, and Hadoop.
In the end, you will have to submit a project as well. Prerequisites include computers science basics, data wrangling, descriptive statistics, R machine learning. Therefore its an advanced level project.
You will learn deeply concepts of data science in this course. The course gives a broad introduction to various concepts of data science. It consists of twitter sentiment analysis in python which is a quite challenging task.
Prerequisites include python, statistics, and SQL, You will learn about relational databases, NoSQL and MapReduce. This is also an advanced course, hence not recommended for beginners. Its duration continues to 3 months.
This course is designed for statistics learning. It will give you an opportunity to learn inferential and descriptive concepts in R. This course is good for learning R and statistics deeply for data science. Course length is 13 weeks.
Kirill Eremenko teaches data science step by step in this course. He will give real analytics examples with training on modeling, tableau visualization and data mining.
You will learn data modeling, data visualization with the help of tools such as SQL, Greta, Tableau. It is considered as one of the best online learning data science courses.
Jose Portilla has designed this amazing course. It will make you understand the use of python for data analysis, working on visualization and the use of powerful machine learning algorithm. It will help you learn Pandas, Plotly, sci-kit learn, Matplotlib, seaborn and Numpy.
Google cloud experts have designed this data engineering certification. You will learn systems for processing data.
Also, you will work with unstructured structured and streaming data. It is part of official google cloud platform training. It uses machine learning models like cloud ML and sensor flow. The total duration of this course is 5 weeks.
I am sure you have got enough information about the popular data science learning courses available online. If you have learned some courses from any other source. Please comment below.