Summary of Python for Data Science Certificate Course

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Python for Data Science Certificate Course

Skill Level: Beginner

Course Overview

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1. INTRODUCTION TO DATA SCIENCE

1. Introduction to Data Science

1.2 Real Life examples with Applications

1.3 Data Scientist Job roles and responsibilities

1.4 The most promising Job of the 21st Century

1.5 Machine Learning vs. Data Science vs. AI

Quiz M1 - Introduction to Data Science

2. Introduction to Python

2.1 Python Introduction

2.2 Installation of Anaconda Navigator

2.3 Jupyter Notebook Interface

2.4 How to Open ,save and Rename a file

2.5 Variables and Data Types

2.6 Python Strings

2.7 Loops (Conditional)

2.8 Loops( Iterative while)

2.9 Loops(iterative For)

2.10 Python Functions(Built in, Lambda, User defined functions)

2.11 Lists

2.12 Tuples

2.13 Sets

2.14 Dictionaries in Python

3 .Data Manipulation and Data Analysis Tools

3.1 Numpy Arrays in Python

3.2 Matrices

3.3 Three Dimensional Arrays Indexing and slicing

3.4 Pandas in Python

3.5 Importing CSV ,Excel Files

3.6 Exporting CSV file

4. Python Data Analysis

4.1 Basic descriptive statistics with Numpy and Applying statistical functions on matrices

4.2 Linear Algebra with NumPy

4.3 Numpy Random Numbers

4.4 Probability distributions using NumPy

4.5 Normality test with SciPy

5. Data Visualization in Python

5.1 The Matplotlib package

5.2 Basic matplotlib plots

5.3 Logarithmic Plots

5.4 Scatter Plots

5.5 Three Dimensional plots

5.6 Lag Plots

5.7 Introduction to Autocorrelation plots

5.8 Introduction to Plot.ly

6. Applications in Industries

6.1 In Consultation with industry expert

MCQ Assessment

Practical Assignment

Project Assignment

Discussion Forum

Python for Data Science Certificate Course