Do we need to change the way we learn?
Before you read any further, here is a sneak peak of our new experiential learning product – PocketML.
What is PocketML?
After hosting thousands of offline trainings, writing blogs on a variety of topics and designing online training, we have realized 3 ingredients that differentiate great trainings from normal ones:
- Focussed content with a clear flow of ideas
- Interaction with learners to make the process fun
- Concise content for it to be consumed while you are on the move, specially for the Mobile generation.
We thought let’s try to get all 3 right in 1 product and that is what you just experienced in the previous section.
Introducing PocketML as in “Machine Learning in your Pocket”. In upcoming sections of this article, you will find the first 4 modules on Python using the learning methodology of PocketML.
Let’s start with the Python basics first.
Conditionals in Python
Now that you are comfortable with Python, it’s time to learn about conditionals. Conditional statements like “if” and “else” give more power to you as a data scientist as you can define and check multiple conditions on your data itself.
Loops in Python
Loops are used when you want to repeat a set of instructions. They are a data scientist’s friend when you want to perform data manipulation through rows of data! Click below to learn more about loops.
Functions in Python
Functions are used to organize your Python code so that you can reuse it whenever needed. Here is how functions work:
While we still actively work on traditional online course formats, we believe the format of PocketML enables the community to maximize the learning capacity.
We see both the formats of learning complement each other extremely well. PocketML gets you excited about new topics/platforms/subjects and traditional module makes you go in-depth of this topic.
Your turn to tell us!
Loved it? Liked it? Needs improvement? Did you realize how engaging this format is compared to traditional online learning modules?
We will love to hear from you so that we can improve before we launch PocketML. What you just learned is all you need to know to start using Python.
Give us your feedback in the comments section below!You can also read this article on our Mobile APP