Machine Learning & Data Science Using Python
Learn with Arpan Gupta |Data Scientist | IITian
8 modules
English
Lifetime access
Master machine learning and data science with Python
Overview
Course Description: Machine Learning & Data Science Using Python In this comprehensive course on Machine Learning and Data Science, you will dive into the world of Python to understand and apply various techniques in data analysis, machine learning, and predictive modeling. Whether you are a beginner or have some experience in programming, this course will equip you with the necessary knowledge and skills to effectively solve real-world problems using Python. Starting with the basics, you will learn about the fundamentals of Python programming, data types, variables, control structures, and functions. You will then explore the power of Python libraries such as NumPy, Pandas, and Matplotlib, which are essential tools for data manipulation, analysis, and visualization. Once you have a strong foundation in Python, you will delve into the core concepts of Machine Learning. You will understand the different types of machine learning algorithms, including supervised and unsupervised approaches, and learn how to train and evaluate models. You will gain insights into exploratory data analysis, hypothesis testing, and regression analysis. Throughout the course, you will work on practical projects that replicate real-life scenarios, allowing you to witness the impact and practical applications of Machine Learning and Data Science. By the end of the course, you will be proficient in Python programming, possess a strong understanding of machine learning algorithms, and be able to apply statistical analysis techniques to extract insights from data. Whether you aspire to become a data scientist, machine learning engineer, or simply want to enhance your analytical skills, this course will empower you with the knowledge and tools needed to excel in the rapidly evolving field of Machine Learning and Data Science using Python.
Key Highlights
Learn machine learning algorithms
Apply data science techniques
Hands-on experience with real-world data
Use Python libraries for data analysis
Build predictive models
What you will learn
Learn machine learning algorithms
Understand the fundamentals of popular machine learning algorithms, including linear regression, logistic regression, decision trees, random forests, and support vector machines.
Apply data science techniques
Learn how to analyze and extract valuable insights from structured and unstructured data using statistical and exploratory data analysis techniques.
Hands-on experience with real-world data
Work with real-world datasets to gain practical experience in data preprocessing, feature engineering, and data visualization.
Use Python libraries for data analysis
Become proficient in using popular Python libraries such as scikit-learn, pandas, and numpy for data manipulation, preprocessing, and building predictive models.
Build predictive models
Learn how to train, evaluate, and tune machine learning models to build accurate predictive models for various data problems.
Modules
Applications of DS & ML
1 attachment • 4.96 mins
Applications of Data Science and Machine Learning
Use Cases of Data Science and Machine Learning
2 attachments • 7.24 mins
Ecommerce Company
Google Self Driving Car
Machine Learning & Types of it
2 attachments • 15.49 mins
Basics of Machine Learning
Types of Machine Learning Techniques
Python Basics for Data Science
2 attachments • 11.37 mins
How to install Python using Anaconda
Introduction to Python Libraries
Python Important Data Structures and Functions
12 attachments • 1 hrs
What is Set in Python
Range Function
List in Python
Append method in List
How to join two list
What is Dictionary in Python
How to Sort list
Enumerate function
What is List Comprehension
What is Map & Lambda Function
How to write something in a text file
What are Classes and Objects in Python
End to End Machine Learning Project -step by step
14 attachments • 42.85 mins
Introduction to the Project
Downloading the data set
Introduction to the dataset
How to import libraries
How to read the dataset
Basic Data Exploration -1
Basic Data Exploration -2
Basic Data Exploration -3
Basic Data Exploration -4
Data Cleaning
Independent Variables/Features & Target Variable
Defining Machine Learning Model
Performing CrossValidation
Final Step-Predictions for Test data set
Other Optional Videos
1 attachment • 4.12 mins
Difference between linear and logistic Regression
FAQs
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Can I access the course materials on any device?
Yes, our platform is designed to be accessible on various devices, including computers, laptops, tablets, and smartphones. You can access the course materials anytime, anywhere, as long as you have an internet connection.
How can I access the course materials?
Once you enrol in a course, you will gain access to a dedicated online learning platform. All course materials, including video lessons, lecture notes, and supplementary resources, can be accessed conveniently through the platform at any time.
Can I interact with the instructor during the course?
Absolutely! we are committed to providing an engaging and interactive learning experience. You will have opportunities to interact with them through our community. Take full advantage to enhance your understanding and gain insights directly from the expert.
About the creator
Learn with Arpan Gupta |Data Scientist | IITian
Arpan Gupta is a postgraduate from Indian Institute of Technology Roorkee.He is passionate about Science in general .He has years of coorporate experience as a data scientist .Leverage his knowledge for your career growth.
Elevate your learning experience with Arpan , a passionate expert in Software & Technology. Immerse yourself in a diverse collection of courses, vibrant communities, insightful webinars, and premium digital products. Start your educational journey today!
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