Python for Data Science and Machine Learning
Abdur Rahman (Joy)

Abdur Rahman (Joy)

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Python for Data Science and Machine Learning (3rd Batch)

Online: TK 10000

Start Date : 2020-09-03  
End Date : 2020-12-03

Total Class : 20   Total Hours: 60

Location : D F Tower (Level-11A) Skill Jobs Digital Lab Skill Jobs Digital Lab, House # 11 (Level-11A), Road # 14, Dhanmondi, Shobhanbag, Dhaka-1209

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Course Description

Python is a general-purpose programming language that is becoming more and more popular for doing data science. Companies worldwide are using Python to harvest insights from their data and get a competitive edge. Unlike any other Python tutorial, this course focuses on Python specifically for data science. In our Intro to Python class, you will learn about powerful ways to store and manipulate data as well as cool data science tools to start your own analyses


Data Science and Machine Learning

This course will enable you to gain the skills and knowledge that you need to successfully carry-out real-world data science and machine learning projects.


The first part of the course covers data analysis and visualization. You will be working on real datasets using Python’s Numpy, Pandas, Matplotlib and Seaborn libraries.


The second part of the course focuses on machine learning. We will be covering both supervised and unsupervised learning. We will be working on case studies from a wide range of verticals including finance, heath-care, real estate, sales, and marketing. Some of the algorithms that will be discussed include Linear Regression, Logistic Regression, Support Vector Machines (SVM), and K-means clustering. This course is the foundation for Deep Learning courses in this specialization.


Course Content

Course Details

Becoming a Data Science Engineer puts you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond. Data Science will impact all segments of daily life by 2025, with applications in a wide range of industries such as healthcare, transportation, insurance, transport and logistics and even customer service. The need for Data Science specialists exists in just about every field as companies seek to give computers the ability to think, learn and adapt.

Total course duration 54 hrs

Core Python

Duration 24 Hrs.

Course Content

Class 1-3


The Python Environment

Starting Python

Using the interpreter

Running a Python script

Python scripts on Unix/Windows

Editors and IDEs


Getting Started

Using variables

Built-in functions



Converting among types

Writing to the screen

Command line parameters

Input from keyboard


Flow Control


About flow control

White space

Conditional expressions

Relational and Boolean operators

While loops

Alternate loop exits


Class 4-8

Lists and Tuples

About sequences

Lists and list methods


Indexing and slicing

Iterating through a sequence

Sequence functions, keywords, and operators

List comprehensions

Nested sequences


Dictionaries and Sets

About dictionaries

Creating dictionaries

Iterating through a dictionary

About sets

Creating sets

Working with sets



About sequences

Function parameters

Global variables

Global scope

Returning values

Sorting data


Using Modules

The import statement

Module search path

Zipped libraries

Creating Modules

Function and Module aliases


Course Introduction for Data Science

Durations 30 Hrs


Class 9-11


Environment Set-Up

  • Jupyter Notebook Installation

 Python for Data Analysis – NumPy

  • Numpy Arrays
  • Numpy Array Indexing
  • Numpy Operations



Class 12-13


Python for Data Analysis – Pandas

  • Series
  • Missing Data
  • Group by
  • Merging Joining and Concatenating
  • Operations
  • Data Input and Output


Class 14-15


Python for Data Visualization – Matplotlib


Class 16-17


Python for Data Visualization – Seaborn

  • Distribution Plots
  • Categorical Plots
  • Matrix Plots
  • Regression Plots
  • Grid
  • Style and Color

Class 8-11

Review class