Learn Complete Data Science & Machine Learning Course
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late. Scroll Down and click Enroll Now button to get enrolled
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Apply Coupon Code: 8C9E45D839547CD8C931
What you’ll learn
- Master the essential concepts, techniques, and tools of data science and machine learning.
- Acquire hands-on experience with Python programming and its libraries for data manipulation, analysis, and visualization.
- Build and evaluate predictive models using a variety of machine learning algorithms and techniques.
- Complete Data Science & Machine Learning Course
This course includes:
- 4 hours on-demand video
- Assignments
- 1 downloadable resource
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Course content
4 sections • 65 lectures • 4h 11m total lengthCollapse all sections
Introduction To Complete Data Science & Machine Learning Course
- Introduction To Course
Complete Python Programming Course
- Python Complete Course Introduction
- Python Class 1 : Introduction To Python
- Python Class 2 : Setting Python Environment
- Python Class 3 : Introduction To Variables
- Python Class 4 : Introduction To Keywords
- Python Class 5 : Introduction To Datatypes
- Python Class 6 : ID Function
- Python Class 7 : Arithmetic Operator
- Python Class 8 : Logical Operator
- Python Class 9 : Comparison Operator
- Python Class 10 : Bitwise Operator
- Python Class 11 : Membership Operator
- Python Class 12 : Identity Operator
- Python Class 13 : Conditional Statements
- Python Class 14 : For Loop and Range Function
- Python Class 15 : While Loops
- Python Class 16 : Break and Continue
- Python Class 17 : Function
- Python Class 18 : Try Except Finally Blocks
- Python Class 19 : String and Functions
- Python Class 20 : List and Functions
- Python Class 21 : Tuple and Functions
- Python Class 22 : Dictionary and Functions
- Python Class 23 : Class and Object
- Python Class 24 : Class Methods
- Python Class 25 : Inheritance and its types
- Python Class 26 : Polymorphism and its types
- Python Class 27 : Encapsulation and Access Modifiers
- Python Class 28 : Abstraction
- Python Class 29 : Mini Project
- Python Assignment
Complete Data Science Course
- Complete Data Science Course
- Numpy Complete Course
- Numpy Class 1 : Import and Install
- Numpy Class 2 : Array and its Types
- Numpy Class 3 : Datatypes
- Numpy Class 4 : NDIM Function
- Numpy Class 5 : ARANGE Function
- Numpy Class 6 : CONCATENATE Function
- Numpy Class 7 : NDMIN Function
- Numpy Class 8 : NDITER Function
- Numpy Class 9 : All Functions
- Pandas Class 1 : Import Dataset
- Pandas Class 2 : Head & Tail Function
- Pandas Class 3 : Info Function
- Pandas Class 4 : Drop na Function
- Pandas Class 5 : Fill na Function
- Pandas Class 6 : Drop Duplicates Function
- Pandas Class 7 : Replace Values Function
- Matplotlib Class 1 : Import Dataset
- Matplotlib Class 2 : Show Function
- Matplotlib Class 3 : Marker Function
- Matplotlib Class 4 : Xlabel Ylabel Function
- Matplotlib Class 5 : Title Function
- Matplotlib Class 6 : Linestyle Linewidth Function
- Matplotlib Class 7 : Barplot
- DATA SCIENCE ASSIGNMENT
Complete Machine Learning Course
- Complete Machine Learning Introduction
- Machine Learning Class 1 : Linear Regression
- Machine Learning Class 2 : Logistics Regression
- Machine Learning Class 3 : Support Vector Machine
- Machine Learning Class 4 : KNN
- Machine Learning Class 5 : K Means Clustering
- Machine Learning Class 6 : Naive Bayes
- Machine Learning Class 7 : Decision Tree Classifier
- Machine Learning Class 8 : Random Forest
- MACHINE LEARNING QUESTIONS
- ML MCQ
Requirements
- python installed
Description
Course Title: Complete Data Science and Machine Learning Course
Course Description:
Welcome to the “Complete Data Science and Machine Learning Course”! In this comprehensive course, you will embark on a journey to master the fundamentals of data science and machine learning, from data preprocessing and exploratory data analysis to building predictive models and deploying them into production. Whether you’re a beginner or an experienced professional, this course will provide you with the knowledge and skills needed to succeed in the dynamic field of data science and machine learning.
Class Overview:
- Introduction to Data Science and Machine Learning:
- Understand the principles and concepts of data science and machine learning.
- Explore real-world applications and use cases of data science across various industries.
- Python Fundamentals for Data Science:
- Learn the basics of Python programming language and its libraries for data science, including NumPy, Pandas, and Matplotlib.
- Master data manipulation, analysis, and visualization techniques using Python.
- Data Preprocessing and Cleaning:
- Understand the importance of data preprocessing and cleaning in the data science workflow.
- Learn techniques for handling missing data, outliers, and inconsistencies in datasets.
- Exploratory Data Analysis (EDA):
- Perform exploratory data analysis to gain insights into the underlying patterns and relationships in the data.
- Visualize data distributions, correlations, and trends using statistical methods and visualization tools.
- Feature Engineering and Selection:
- Engineer new features and transform existing ones to improve model performance.
- Select relevant features using techniques such as feature importance ranking and dimensionality reduction.
- Model Building and Evaluation:
- Build predictive models using machine learning algorithms such as linear regression, logistic regression, decision trees, random forests, and gradient boosting.
- Evaluate model performance using appropriate metrics and techniques, including cross-validation and hyperparameter tuning.
- Advanced Machine Learning Techniques:
- Dive into advanced machine learning techniques such as support vector machines (SVM), neural networks, and ensemble methods.
- Model Deployment and Productionization:
- Deploy trained machine learning models into production environments using containerization and cloud services.
- Monitor model performance, scalability, and reliability in production and make necessary adjustments.
Enroll now and unlock the full potential of data science and machine learning with the Complete Data Science and Machine Learning Course!
Who this course is for:
- Students and professionals interested in pursuing a career in data science, machine learning, or artificial intelligence.
- Professionals seeking to enhance their skills and stay competitive in the rapidly evolving field of data science and machine learning.
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Note: The course is free for a limited time and limited to 500 users. Enroll as soon as possible. If it is no longer free, it means you are late, and it has already exceeded its limits.
🎫 After adding the course into Cart at Checkout page, Apply Coupon Code➛. 8C9E45D839547CD8C931 Note:- After applying coupon, if it says ”This coupon has exceeded its maximum possible redemptions…”, then it means you’re Late, and first 500 coupons already redeemed.
