Course Description :

We are delighted to welcome you into the Python for Data Science Course of ISS Campus Colombo.
Python for Data Science. In this course, you will learn both the basics of
conducting data science and how to perform data analysis in python step by step.

First, and foremost, you’ll learn how to conduct data science by learning how to analyze data. That includes knowing how to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily shareable reports. We’ll also introduce you to two powerful areas of data analysis: machine learning and natural language processing. To conduct data analysis, you’ll learn a collection of powerful, open-source, tools including:

Prerequisites :

This course is intended for learners who have a basic knowledge of programming in any
language (Java, C, C++, Javascript, PHP, python, etc.).

Your knowledge need not be extensive, but our teachers will assume you already know how to:
● Create an assign variables.
● Write programs with loops
● Write programs with conditions
● Author and use functions (methods)

If you are not familiar with Python or Programming Concepts, You do not need to worry, just join our Python Essential Training course.

Syllabus:

● Class 1 – Introduction:
Welcome and overview of the course. Introduction to the data
science process and the value of learning data science.

● Class 2 – Background:
In this optional week, we provide a brief background in python
to get you up and running. If you are already familiar with python then we can do a quick re-cap.

● Class 3 – Jupyter and Numpy:
Jupyter notebooks are one of the most commonly used
tools in data science as they allow you to combine your research notes with the code for
the analysis. After getting started in Jupyter, we’ll learn how to use numpy for data
analysis. numpy offers many useful functions for processing data as well as data
structures which are time and space efficient.

● Class 4 – Pandas:
Pandas, built on top of numpy, adds data frames which offer critical
data analysis functionality and features.

● Class 5 – Visualization:
When working with large datasets, you often need to visualize
your data to gain a better understanding of it. Also, when you reach conclusions about
the data, you’ll often wish to use visualizations to present your results.

● Class 6 – Mini Project:
With the tools of Jupyter notebooks, numpy, pandas, and
Visualization, you’re ready to do sophisticated analysis on your own. You’ll pick a
dataset we’ve worked with already and perform an analysis for this first project.

● Class 7 – Machine Learning:
To take your data analysis skills one step further, we’ll
introduce you to the basics of machine learning and how to use sci-kit learn – a powerful
library for machine learning.

● Class 8 – Working with Text and Databases:
You’ll find yourself often working with text data or data from databases. This week will give you the skills to access that data. For text data, we’ll also give you a preview of how to analyze text data using ideas from
the field of Natural Language Processing and how to apply those ideas using the Natural
Language Processing Toolkit (NLTK) library.

● Class 9 and 10 – Final Project: These weeks let you showcase all your new skills in an
end-to-end data analysis project. You’ll pick the dataset, do the data munging, ask the
research questions, visualize the data, draw conclusions, and present your results.

Total Fees: 30,000/=
Total Duration: 20 Hrs (2 hours  x  10 Classes)
Training Mode: Individual Training, your own timetable

Live Online Classes  or Face to Face Direct Classes with our expert trainers.
Call +94 (0) 722000999 / +94 (0) 755123111 www.iss.lk. Medium : සිංහල / தமிழ் / English