We have opened the enrollment for this November’s Data Science Booster training!
It’s a 10 hrs online training with 5 days (2 hours / day) to learn various Data Science topics in a hands-on format.
Check out the training page for more details!
At the end of the training, you will be able to:
- Understand the benefit of Data Science methods, how to use them, when to use them, and most importantly why you want them.
- Use the Data Science methods effectively to gain deeper business insights from the real world data that are useful for making business decisions.
- Communicate your insights - what they are, how you discover and conclude, why they are important - with others effectively.
Date:2023/11/13(Mon), 11/14(Tue), 11/15(Wed), 11/16(Thu), 11/17(Fri)
Time: Starts at Noon ET / 9AM PT / 5PM GMT / 6PM CET
Total Time: 10 hrs of online classes (2 hrs a day) plus exercise homework.
Price: US $495
Early Bird: US$445 (10% Off) - Until 9/30/2023
Student discount (50% off) available. Click here.
It will include 6-month subscription of Exploratory Desktop - Personal Edition and the training materials. This will give you enough time and environment to keep improving your Data Science skills by applying what you have learned in the training to your real world data.
This training would be perfect if you :
- Want to learn how to apply Data Science in the real world business scenario.
- Want to start a journey of becoming a Data Scientist.
- Want to start Data Science projects but don’t know where to start.
- Wanted to learn Data Science before, but gave up due to the steep learning curve of learning programming and/or statistics.
What you need before the training
- Being able to use Excel (or any other spreadsheet tools) and perform the basic calculations (e.g. sum, average, etc.).
- Being curious about Data.
- Having a desire and commitment to learn how to understand data better.
- Positive attitude towards learning something new.
What you don’t need before the training
- Programming skill (if you have, of course, you can do a lot more down the road, but not necessary for this training.)
- Statistics background (if you have, of course, that makes things easier, but not necessary for this training.)
- Negative attitude towards learning something new.