For those looking for free Analytics & Data Science Training, here are some upcoming sessions that may be of interest:

• Explore Statistics with R (Starts: Self-Paced): Learn basic statistics in a practical, experimental way, through statistical programming with R, using examples from the health sciences.

Do you want to learn how to harvest health science data from the Internet? Or learn to understand the world through data analysis? Start by learning R Statistics!

Skilled professionals who can process and analyze data are in great demand today. In this course you will explore concepts in statistics to make sense out of data. You will learn the practical skills necessary to find, import, analyze and visualize data. We will take a look under the hood of statistics and equip you with broad tools for understanding statistical inference and statistical methods. You will also perform some really complicated calculations and visualizations, following in the footsteps of Karolinska Institute’s researchers.

Statistical programming is an essential skill in our golden age of data abundance. Health science has become a field of big data, just like so many other fields of study. New techniques make it possible and affordable to generate massive data sets in biology. Researchers and clinicians can measure the activity for each of 30000 genes of a patient. They can read the complete genome sequence of a patient. Thanks to another trend of the decade, open access publishing, the results of such large scale health science are very often published for you to read free of charge. You can even access the raw data from open databases such as the gene expression database of the NCBI, National Center for Biotechnology Information.

We will dive into this data together. Learn how to use R, a powerful open source statistical programming language, and see why it has become the tool of choice in many industries in this introductory R statistics course.

• Predictive Analytics (Starts: November 25, 2015): Master the tools of predictive analytics in this statistics based analytics course.

Decision makers often struggle with questions such as: What should be the right price for a product? Which customer is likely to default in his/her loan repayment? Which products should be recommended to an existing customer? Finding right answers to these questions can be challenging yet rewarding.Predictive analytics is emerging as a competitive strategy across many business sectors and can set apart high performing companies. It aims to predict the probability of the occurrence of a future event such as customer churn, loan defaults, and stock market fluctuations – leading to effective business management.

Models such as multiple linear regression, logistic regression, auto-regressive integrated moving average (ARIMA), decision trees, and neural networks are frequently used in solving predictive analytics problems. Regression models help us understand the relationships among these variables and how their relationships can be exploited to make decisions.

This course is suitable for students/practitioners interested in improving their knowledge in the field of predictive analytics. The course will also prepare the learner for a career in the field of data analytics. If you are in the quest for the right competitive strategy to make companies successful, then join us to master the tools of predictive analytics.

• Learn to Program Using Python (Starts: January 10, 2016): Hands on introduction to the Python programming language.

Interested in learning a computer programming language but unsure of how and where to begin? This course, Learn to Program Using Python, is a great place to start. Python is an easy and fun language to learn, and it is now one of the most popular programming languages, suitable for almost any task from developing graphical user interfaces to building web applications.

This course is an introduction to the Python programming language. This course is open to all learners who wish to gain an understanding of the basic components of computer programming. You will learn basic computer programming concepts and terminologies such as variables, constants, operators, expressions, conditional statements, loops, and functions. This Python course includes hands-on exercises to help you understand the components of Python programming while incrementally developing more significant programs. The exercises in this course will be based on small assignments which will relate to real-world problems.  No previous programming knowledge needed.

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