Why Should you learn Python?
The Python programming language is currently fuelling scientific programming, but this wasn’t always the case. For years academic scholars and private researchers were using the MATLAB language for scientific research. That all started to change with the release of Python numerical computation engines such as NumPy. allowing complex calculations to be done by a single “import” statement followed by a function call.
Slowly but surely, Python started to take over as the preferred language for data analytics and machine learning. Python is the future of Artificial Intelligence.
Given the flexibility of the language, its speed, and the machine learning functionality, we’ll continue to see Python dominate the machine learning landscape.
What is covered in this course?
This course is the complete guide to take you from a beginner in Python to an expert in data analysis and visualization.
Why learn from us?
Why Should you learn Python?
The Python programming language is currently fuelling scientific programming, but this wasn’t always the case. For years academic scholars and private researchers were using the MATLAB language for scientific research. That all started to change with the release of Python numerical computation engines such as ...
|Section 1: Introduction|
|1||About the course||00:03:13|
|4||Writing your first code in Python||00:04:01|
|5||All about Jupyter Notebook||00:05:22|
|Section 2: Python Building Blocks|
|4||String Data Type - 1||00:02:54|
|5||String Data Type - 2||00:02:37|
|6||String Data Type - 3||00:03:24|
|7||String Data Type - 4||00:02:39|
|8||String Data Type - 5||00:03:13|
|9||String Data Type - 6||00:12:50|
|Section 3: Data Structures|
|1||Introduction to List data type||00:07:48|
|2||Methods in List Data type||00:09:41|
|Section 4: Flow control statements and Functions|
|1||IF-ELSE, WHILE and FOR||00:13:00|
|2||Functions - Basics||00:04:28|
|Section 5: File Input/Output|
|1||File handling - read operations||00:05:10|
|2||File handling - write operations||00:03:45|
|Section 6: Object Oriented Programming|
|1||Classes and Objects||00:06:38|
|Section 7: Errors and Exceptions|
|1||All about errors and exceptions||00:09:36|
|2||Raise and Assert Statements||00:03:41|
|Section 8: Text mining using Regular Expressions|
|1||Introduction to regular expressions||00:04:21|
|2||Extracting numbers from text||00:04:12|
|4||Meta characters and extracting email addresses||00:08:15|
|Section 9: NumPy|
|2||Indexing and Slicing||00:05:47|
|3||Mathematical Operations- Universal Functions||00:05:54|
|4||Sort Combine and Split arrays||00:08:17|
|Section 10: Pandas|
|2||Data frame attributes||00:05:02|
|3||Reading and Writing data frame||00:05:57|
|4||Index Slice Drop Data frame||00:05:55|
|5||Sorting and Filtering||00:11:25|
|Section 11: MatplotLib|
|2||Object Oriented Plotting||00:05:10|
|3||Formatting a plot||00:06:00|
Yes..good so far and to the point
Good course... Detailed explanation is the best part of this python course.
The instructor seems knowledgeable and the content is easy to follow.
Good course content
Awesome course..concepts are explained brilliantly. Thanks