Advance Python | Python for Datascience

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Prashant Mishra

9:44:02

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1. Introduction to Python

1. Introduction to python (part-1).mp4

27:45

2. Introduction to python (part-2).mp4

27:53

2. Advanced Python Concepts

1. List Comprehension and Generators.mp4

24:11

2. File Handling.mp4

18:02

3. Exception handling.mp4

15:15

4. Object Oriented Programming (oops).mp4

26:38

5. Decorators and Metaclasses.mp4

16:11

3. NumPy (expand on the basic library coverage)

1. Arrays and Arrays Operations.mp4

31:44

2. Array Indexing and Slicing.mp4

29:46

3. Broadcasting and Vectorization.mp4

26:47

4. Mathematical functions and Linalg.mp4

22:01

5. Array Manipulation and Reshaping.mp4

23:00

4. Pandas (expand on the basic library coverage)

1. Pandas Datastructure.mp4

23:32

2. Data Transformation and Manipulation.mp4

23:43

3. Data Cleaning and Preprocessing.mp4

29:34

4. Joining Merging and Reshaping.mp4

22:59

5. Data Visualization

1. Advanced Matplolib Techniques.mp4

28:12

2. Seaborn.mp4

20:57

3. Plotly.mp4

28:56

4. Geospatial Data Analysis.mp4

25:34

6. Supervised Learning Algorithms

1. Linear Regression.mp4

24:24

2. Logistic Regression.mp4

16:00

3. Support Vector Machines, Decision Trees, Random Forests,.mp4

24:00

7. Unsupervised Learning Algorithms

1. 24. Unsupervised Learning.mp4

26:58

Description

A Python-Based Datascience Roadmap

What You'll Learn?

The course is designed to provide students with a strong foundation in advanced Python programming, data analysis, and machine learning.
Students will learn advanced programming concepts, including list comprehensions, file I/O operations, exception handling, and lot more advance python concepts.
Data manipulation and analysis using the NumPy and Pandas libraries, covering data cleaning, preprocessing, and transformation techniques.
Data visualization using Matplotlib, Seaborn, and Plotly for creating informative and visually appealing plots and charts.
Implementation and evaluation of various machine learning algorithms, such as supervised and unsupervised learning, using the Scikit-learn library.
Optional exploration of advanced topics like natural language processing, web scraping, time series analysis, and recommender systems for a more comprehensive u

Who is this for?

Students interested in exploring data analysis, cleaning, and preprocessing techniques using Python will find this course helpful in understanding how to work w

For students keen on expanding their knowledge beyond basic programming, this course delves into advanced Python concepts, object-oriented programming, and more

Students those who wants to learn advanced Python concepts, and are intrested towards the field of datascience

Students and professionals in the field of machine learning and artificial intelligence looking to strengthen their understanding of Python for implementing and

Data analysts and data scientists seeking to leverage Python for advanced data manipulation, analysis, and visualization tasks.

Intermediate Python developers aiming to enhance their skills and delve deeper into advanced programming concepts.

Software engineers interested in expanding their knowledge of Python for various applications, including web development, data processing, and automation.

What You Need to Know?

Students should have understanding of fundamental Python concepts, including variables, data types, loops, and functions.

A genuine interest in working with data, conducting data analysis, and implementing machine learning models is crucial to fully benefit from the course content.

A foundational knowledge of basic mathematical concepts, such as algebra and statistics, will be helpful for comprehending certain aspects of data analysis, machine learning, and numerical computing.

More details

Description
Ready to advance your Python skills? Our easy-to-follow Advanced Python course is tailored for learners of all levels, This course is crafted for students aspiring to master Python and dedicated to pursuing careers as data analysts or data scientists. It comprehensively covers advanced Python concepts, providing students with a strong foundation in programming and data analysis, focusing on data analysis, visualization, and machine learning.
Discover the power of Python in handling complex data, creating engaging visuals, and building intelligent machine-learning models.
Course Curriculum:
1. Introduction to Python:
Part 1: Dive into Python fundamentals (27:42)
Part 2: Further exploration of Python basics (27:49)
2. Advance Python Concepts:
List Comprehension and Generators (24:07)
File Handling (17:58)
Exception Handling (15:12)
Object-Oriented Programming (OOPs) (26:34)
Decorators and Metaclasses (16:06)
3. NumPy (Expanded Library Coverage):
Arrays and Array Operations (31:38)
Array Indexing and Slicing (29:39)
Broadcasting and Vectorization (26:43)
Mathematical Functions and Linear Algebra (21:55)
Array Manipulation and Reshaping (22:52)
4. Pandas (Expanded Library Coverage):
Pandas Data Structures (23:26)
Data Transformation and Manipulation (23:36)
Data Cleaning and Preprocessing (29:30)
Joining, Merging, and Reshaping (22:56)
5. Data Visualization:
Advanced Matplotlib Techniques (28:08)
Seaborn for Statistical Visualization (20:53)
Plotly for Interactive Visualizations (28:52)
Geospatial Data Analysis (25:31)
6. Machine Learning with Scikit-learn (Expanded Library Coverage):
Linear Regression (24:19)
Logistic Regression (15:55)
SVM, Decision Tree, Random Forest (23:56)
Unsupervised Learning (26:54)
Model Validation Techniques (23:10)
Hyperparameter Tuning and Model Selection (30:49)
7. Case Studies and Projects:
House Rent Prediction (55:10)
Heart Disease Prediction (44:28)
Customer Segmentation (12:41)
Â Â Why Choose Our Course?
In-depth Modules Covering Python, NumPy, Pandas, Data Visualization, and Machine Learning
Hands-on Learning with Real-world Case Studies
Expert-led Sessions for Comprehensive Understanding
Unlock Your Potential in Data Science and Python Programming

With hands-on practice and expert guidance, you'll be prepared for rewarding opportunities in data science and analytics.

Â Â Join us now to become a proficient Python data analyst and unlock a world of possibilities!Â Â

Who this course is for:
Students interested in exploring data analysis, cleaning, and preprocessing techniques using Python will find this course helpful in understanding how to work w
For students keen on expanding their knowledge beyond basic programming, this course delves into advanced Python concepts, object-oriented programming, and more
Students those who wants to learn advanced Python concepts, and are intrested towards the field of datascience
Students and professionals in the field of machine learning and artificial intelligence looking to strengthen their understanding of Python for implementing and
Data analysts and data scientists seeking to leverage Python for advanced data manipulation, analysis, and visualization tasks.
Intermediate Python developers aiming to enhance their skills and delve deeper into advanced programming concepts.
Software engineers interested in expanding their knowledge of Python for various applications, including web development, data processing, and automation.

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I am Computer Science Graduate in 2021 and with a passion for teaching, started back as a BDA in various Ed-tech companies, which increased a little more passion towards this industry to explore.Have trained more than 5000+ Individual students one-on-one and group-based, which not only found my classes very interesting but also developed a huge scope of job opportunities in the future.

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