Python for Data Science: Python Programming & Data Analysis

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Start-Tech Academy,Start-Tech Trainings

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1. Introduction

1. Introduction.mp4

02:09

2.1 Python training.zip

2. Course resources.html

2. Getting Started with Python

1. Introduction to Python.mp4

06:03

2. First code to Python Programming.html

3. Variables in Python Declaration and Use.mp4

11:10

4. Basic Arithmetic Operations in Python.html

5. Data types in Python.mp4

08:32

6. Python String.mp4

09:09

7. Quiz.html

8. String methods.mp4

14:41

9. Calculating Body Mass Index (BMI) in Python.html

10. Practice Assignment.html

3. Data Structures in Python

1. List in Python.mp4

14:01

2. Working with Lists in Python.html

3. Tuples in Python.mp4

08:09

4. Dictionaries in Python.mp4

06:12

5. Working with Dictionaries in Python.html

6. Sets in Python.mp4

05:32

7. Practice Assignment.html

4. Conditional Statements in Python

1. Python Conditional Expressions.mp4

06:15

2. Conditional Statements in Python.html

3. Exploring Operators and Conditional Expressions in Python.mp4

14:06

4. Practice Assignment.html

5. Loops in Python

1. For loops in Python.mp4

15:24

2. Generating Square Numbers in Python.html

3. While loops in Python.mp4

11:53

4. Practice Assignment.html

6. Python Functions

1. Function in Python.mp4

13:09

2. Checking Even Numbers Using Functions in Python.html

3. Recursion in Python.mp4

10:25

4. Lambda function.mp4

10:41

5. Lambda Functions for Exponentiation.html

6. Practice Assignment.html

7. File handling in Python

1. File IO in Python.mp4

13:59

2. Writing to a File in Python.html

3. Quiz.html

8. NumPy Library

1. Introduction to NumPy arrays.mp4

10:03

2. Accessing the elements of NumPy arrays.mp4

08:02

3. Creating and Accessing Elements in NumPy Arrays.html

4. Leveraging Data Types, Shapes, and Array Stacking in NumPy.mp4

12:02

5. Exploring Diverse Approaches to Creating NumPy Arrays.mp4

07:44

6. Creating NumPy Arrays with Evenly Spaced Numbers.html

7. Mathematical operations on arrays.mp4

08:07

8. Array Operations and Median Calculation in Python.html

9. Practice Assignment.html

9. Pandas Library

1. Introduction to Pandas Library.mp4

04:41

2. Creating DataFrame from Dictionary in Pandas.html

3. Exploring Series and DataFrame in Python.mp4

07:32

4. Essential Data Analysis Methods in Python.mp4

13:52

5. Importing Data from CSV File using Pandas.html

6. Missing Data Handling in Python.mp4

13:14

7. Manipulating DataFrame in Python.mp4

17:11

8. Practice Assignment Analyzing and Visualizing the Titanic Dataset with Pandas.html

10. Matplotlib Library

1. Introduction to Matplotlib Library.mp4

05:27

2. Data Visualization with Matplotlib Plotting Essentials and Customization.mp4

15:43

3. Visualizing Average Session Length per Day with a Line Chart.html

4. Exploring Subplots, Scatter Plots, and Customization.mp4

11:22

5. Creating a Scatter Plot of Random Data Points.html

6. Crafting Bar Plots, Histograms, Pie Charts with Customization Using Matplotlib.mp4

12:44

7. Practice Assignment Visualizing Olympic Medals Data with Matplotlib.html

11. Seaborn Library

1. Introduction to Seaborn Library.mp4

08:27

2. Exploring Seaborn Univariate and Bivariate Analysis for Data Visualization.mp4

07:26

3. Advanced Data Visualization with Seaborn Pairplot and Barplot Customization.mp4

10:52

4. Advanced Visualizations with Countplot and Heatmap Using Seaborn.mp4

08:18

5. Practice Assignment Data Visualization with Seaborn and the Iris Dataset.html

12. Conclusion

1. About your certificate.html

2. Bonus lecture.html

Description

Transform data into insights using Python and its powerful Libraries such as Numpy, Pandas, MatplotLib, Seaborn etc.

What You'll Learn?

Gain a thorough understanding of Python syntax, script writing, and fundamental programming concepts such as variables, data types, and string operations
Become adept at using lists, dictionaries, tuples, and sets for organizing and managing data effectively within Python
Master the use of conditional statements and loops in Python to automate and optimize data processing tasks
Learn to design reusable Python functions to perform repetitive tasks efficiently, including knowledge of recursion and lambda functions
Acquire skills in reading from and writing to files in Python, crucial for data processing tasks in real-world applications
Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance
Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format for analysis
Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python

Who is this for?

Aspiring Data Scientists: Beginners who are interested in entering the field of data science and need to build foundational skills in programming and data handling.

Professionals Seeking a Career Transition: Individuals in various fields such as business, finance, or healthcare, who wish to transition into data-centric roles and require practical skills in data manipulation and analysis.

Hobbyists and Personal Learners: Anyone with a curiosity about data science and how Python programming can be applied to sort, analyze, and visualize data in personal projects or informal learning.

Students in STEM Fields: College students or high school seniors who are studying subjects like statistics, mathematics, or computer science and want to enhance their data analysis capabilities.

What You Need to Know?

No prior experience in Python or data analysis is required; just basic computer skills and access to a computer with an internet connection are necessary to start this course.

More details

Description
Are you aspiring to become a data scientist or aiming to enhance your data analysis skills? Have you ever found yourself overwhelmed by data, wondering how to turn it into actionable insights? If your goal is to not only understand the vast world of data science but also to apply this knowledge practically, then this course is designed with you in mind. Dive into the transformative world of Python and its powerful libraries, and start your journey towards becoming a proficient data scientist.
This course offers a comprehensive guide to mastering Python programming and data analysis, tailored specifically for data science applications. By engaging with this course, you will:
Develop a solid foundation in Python programming, from basic syntax to advanced functions.
Master the art of handling and analyzing data using Pythonâ€™s most powerful libraries, including NumPy for numerical data, Pandas for data manipulation, Matplotlib and Seaborn for data visualization.
Create compelling data visualizations that communicate your findings effectively.
Implement data manipulation techniques to clean, transform, and prepare your data for analysis.
Solve real-world data analysis problems by applying practical programming solutions.
Why is learning about this topic crucial?
In todayâ€™s data-driven world, the ability to analyze and interpret data is indispensable. Python, being at the forefront of data science, offers an extensive ecosystem of libraries and tools that make data analysis accessible and powerful. Whether youâ€™re analyzing customer data to inform business decisions, researching for academic purposes, or exploring datasets for personal projects, Python provides the capabilities to turn data into insights.
Throughout this course, youâ€™ll engage in hands-on activities such as coding exercises, real-world data analysis projects, and creating data visualizations. These practical experiences are designed to cement your learning and give you the confidence to apply your skills in a professional setting.
What sets this course apart is not just the breadth of topics covered but the focus on practical application. Youâ€™ll learn not just the theory but how to apply these concepts in real-world scenarios, preparing you for immediate application in your work or studies.
Don't let data overwhelm you any longer. Take the first step towards unlocking its potential by enrolling in Python for Data Science: Python Programming & Data Analysis today. Transform data into insights and become an invaluable asset in the field of data science.
Who this course is for:
Aspiring Data Scientists: Beginners who are interested in entering the field of data science and need to build foundational skills in programming and data handling.
Professionals Seeking a Career Transition: Individuals in various fields such as business, finance, or healthcare, who wish to transition into data-centric roles and require practical skills in data manipulation and analysis.
Hobbyists and Personal Learners: Anyone with a curiosity about data science and how Python programming can be applied to sort, analyze, and visualize data in personal projects or informal learning.
Students in STEM Fields: College students or high school seniors who are studying subjects like statistics, mathematics, or computer science and want to enhance their data analysis capabilities.

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Start-Tech Academy

Instructor's Courses

Start-Tech Academy is a technology-based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners. Our top quality training content along with internships and project opportunities helps students in launching their Analytics journey. Founded by Abhishek Bansal and Pukhraj Parikh. Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics and Python.Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.

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