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Data Science

Data Science with Python Course

12 Weeks

Overview

This Data Science with Python Course is designed to equip learners with the fundamental skills and knowledge needed to harness the power of Python for data analysis, visualization, and machine learning. This course offers a hands-on approach to learning Python, with practical examples, real-world projects, and interactive exercises that will enable you to build robust data-driven solutions. Whether you are a beginner looking to break into the field of data science or an experienced professional seeking to enhance your skill set, this course will provide you with the tools you need to succeed.

Requirements

Basic Knowledge of Python: Familiarity with basic Python syntax and programming concepts is recommended but not required.

Internet Access: Reliable internet access is necessary for participating in online modules, completing assignments, and accessing digital marketing tools and resources.

Software Installation: Python 3.x, Jupyter Notebook, and Anaconda distribution should be installed before the course begins.

Curriculum

Module 1- Data Types and operators

- Python installation using either the jupyter notebook or Spyder Anacondang
- Arithmetic operator Variable
- Integers and Floats
- Boolean Comparison operator
- Strings and String methods

- Lists and membership operators List methods
- Tuples
- Sets Dictionary and Identity Operators
- When to use Dictionaries
- Compound data structures

- Conditional Statements
- Boolean Expression For Conditions
- For-loops Iterating through a Dictionary
- While-loops
- Loop Controls
- List comprehensions

- Defining a Function
- Variable Scopes
- Lambda Expressions
- Documentations

- Configuring Git Bash for python
- Running a python script
- Editing a python script
- Scripting with raw input
- Errors and exception
- Handling errors
- Reading and writing files

- Classes
- Abstraction
- Polymorphism
- Generators
- Iterators
- Encapsulation
- Inheritance

- Creating a numpy array
- Accessing, Deleting and inserting into a numpy array
- Slicing, Boolean indexing, set operations and sorting
- Arithmetic operators and broadcasting

- Introduction to Pandas
- Panda data types, Creating pandas series
- Accessing and deleting elements in a pandas series
- Arithmetic operators in a pandas series
- Manipulating a pandas series

- Creating pandas data frames
- Accessing elements in a pandas data frame
- Dealing with NaN
- Manipulating a data frame
- Loading data into pandas

- Introduction to machine learning
- Types of machine learning algorithms (Supervised and unsupervised)
- Decision trees
- Random Forest
- Supervised learning-Logistic regression

FAQs

This course is for anyone interested in learning Python for data science, regardless of their background. Whether you're a beginner with no programming experience or an experienced professional looking to add Python to your toolkit, this course is designed to cater to all levels.

Basic computer skills and familiarity with the internet are recommended. A passion for Data and a desire to learn are key. No prior data science experience is necessary, as we cover all the essentials from the ground up.

Yes, upon successfully completing the course, you will receive a recognized certificate from BCT Academy, which you can showcase to employers or clients as proof of your expertise.

₦120,000

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Featured Review

Enrolling in the Python for Data Science course at BCT Academy was one of the best decisions I've made for my career. The curriculum was well-structured, and the hands-on projects gave me the confidence to apply what I learned in real-world scenarios. I highly recommend it to anyone looking to break into the field of data science.

— Chidimma, Data Analyst