Python for Data Science
Fundamentals
This is a hands-on and project-based course designed to help you master the foundational skills needed to analyze and visualize Data with Python. This course covers Python Data structures, Conditional statement, loops, comprehensions and Numpy.
Python is one of the top programming languages to learn and most professionals agree that those looking to break into Data Science and Machine Learning should have some python skills under their belt.
From startups to popular platforms such as Instagram, Google, Reddit and YouTube, Python remains a go-to language. With so many employers looking for professionals with Data Skills, learning Python can open up a lot of career opportunities for you. Whether you want to work in machine learning, artificial intelligence (AI), data science or scalable web applications, you’ll need to learn the technology behind it first.
COURSE OVERVIEW
This course is the first course in our 3-part specialization program on Python for Data Science. This course is hands-on and is designed for professionals and graduates who want to learn how to analyze and visualize data using Python.
In this course, you will learn basics Python programming and syntax, loops, strings, lists, dictionaries, and object-oriented programming. You will also learn how to create functions and automate tasks in Python. You will be exposed to the Numpy arrays and array properties some of the operations and attributes of Numpy arrays like reshaping, resizing, indexing and slicing and explore important concepts like vectorization.
Why take this Course?
Python is the main programming language for Data Science. This course is hands-on and designed to help you master the core and the foundational python skills for Data Science and analytics.
This course is designed for absolute Python beginners. It will also be helpful for learners with some knowledge of Python.
COURSE CONTENT
- 54 Lessons
- 5+ Hours on demand videos
- Code samples
- 10+ exercises
WHAT YOU WILL LEARN
This course is hands-on and is designed to equip learners with the practical skills in Python and how Python is applied in Data Science and Data Analytics.
- Work with Python Data structures
- Automate processing and computations using loops and nested loops.
- Create user-defined functions for complex analysis.
- Create conditional logic for decision making
- Work with arrays using Numpy arrays.
- Perform aggregation and summary analysis on data using Numpy.
COURSE REQUIREMENT
- No software or installation is needed. We will use Google Colab which allows you to write and execute Python code within your browser. You just need a google account. We will walk you through how to get started with Colab in this course.
- No prior knowledge in Python is required(prior knowledge of Python will be a plus)
Be future ready.
Develop your Python skills and begin exciting career in the tech space as a Data Scientist, Data Analyst, AI Specialist or Data Engineer.
Google Colab notebooks
Colab Notebooks are Jupyter notebooks that run in the cloud and are highly integrated with Google Drive, making them easy to set up, access, and share.
Colab allows you to write and execute Python in your browser, with
- Zero configuration required
- Free access to GPUs
- Easy sharing
COURSE CURRICULUM:
This course is hands-on and focuses on the key skills you need to master Python for Data Science and Analytics.
- Sample Notebook
- Introduction to Loops (2:05)
- Introduction to for loops demo 1 (3:06)
- Introduction to for loops demo 2 (4:49)
- Introduction to for loops demo 3 (3:21)
- Introduction to for loops demo 4 (6:54)
- Introduction to for loops demo 5 (4:09)
- Iterating over dictionaries (5:50)
- Introduction to Nested Loops (9:52)
- Nested Loops (5:02)
- Introduction to Loops with IF Statement (6:16)
- Iterating over dictionaries with IF Statement (4:42)
- Introduction to WHILE Loops (4:26)
- While loops demo 1 (3:47)
- While loops demo 1 (1:57)
- List comprehension (5:19)
- Enumerate Function (5:27)
- Guided Project: Setting up a login system (13:49)
- Sample Notebook
- Introduction to Arrays (1:38)
- Arrays vs Lists (1:40)
- Creating Arrays (4:36)
- Creating multidimensional arrays (4:31)
- Creating 3 dimensional arrays (3:00)
- Data types (3:04)
- Reshaping arrays (6:01)
- Resize arrays (1:53)
- Indexing arrays (3:05)
- Slicing arrays (4:49)
- Slicing multi dimensional arrays (5:03)
- Vectorization (3:36)
- Basic Numpy operations (3:40)
- Aggregate functions (2:23)
- Aggregate functions and arrays (3:06)
- Mini Project (6:10)
Be future ready.
Develop your Python skills and begin exciting career in the tech space as a Data Scientist, Data Analyst, AI Specialist or Data Engineer.
