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Learna all about Machine Learning!
Updated on Sep, 2026
Programming, Data Science,
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The “Machine Learning” course is an intermediate-level course, curated exclusively for both beginners and professionals. The course covers the basics as well as the advanced-level concepts. The course contains content-based videos along with practical demonstrations that perform and explain each step required to complete the task.
Learning Objectives:
By the end of the course, you will be able to learn about:
Evolution of Artificial Intelligence
Sci-Fi Movies with the Concept of AI
Relationship between Artificial Intelligence, Machine Learning, and Data Science
Definition and Features of Machine Learning
Machine Learning Approaches
Machine Learning Techniques
Applications of Machine Learning
Data Exploration Loading Files
Importing and Storing Data
Data Exploration Techniques
Correlation Analysis
Missing Values in a Dataset
Outlier Values in a Dataset
Outlier and Missing Value Treatment
Functionalities of Data Object in Python
Different Types of Joins
Labor Hours Comparison
Introduction to Supervised Learning
Example of Supervised Learning
Understanding the Algorithm
Supervised Learning Flow
Types of Supervised Learning
Types of Classification Algorithms
Types of Regression Algorithms
Evaluating Coefficients
Challenges in Prediction
Survival of Titanic Passengers
Principal Component Analysis (PCA)
Linear Discriminant Analysis
Overview of Classification
Use Cases of Classification
Classification Algorithms
Decision Tree Classifier
Decision Tree Examples
Decision Tree Formation
Choosing the Classifier
Overfitting of Decision Trees
Random Forest Classifier- Bagging and Bootstrapping
Decision Tree and Random Forest Classifier
Performance Measures: Confusion Matrix
Performance Measures: Cost Matrix
Naive Bayes Classifier
Support Vector Machines : Linear Separability
Support Vector Machines : Classification Margin
Overview of unsupervised learning
Example and Applications of Unsupervised Learning
Introduction to Clustering
Optimal Number of Clusters
Cluster Based Incentivization
Overview of Time Series Modeling
Time Series Pattern Types
Removal of Non-Stationarity
Steps in Time Series Forecasting
Overview of Ensemble Learning
Ensemble Learning Methods
AdaBoost Algorithm and Flowchart
Introduction to XGBoost
Parameters of XGBoost
Pima Indians Diabetes
Common Splitting Strategies
Introduction to recommender system
Purposes of Recommender Systems
Paradigms of Recommender Systems
Collaborative Filtering
Association Rule Mining
Association Rule Mining: Market Basket Analysis
Association Rule Generation: Apriori Algorithm
Apriori Algorithm Example
Apriori Algorithm: Rule Selection
User-Movie Recommendation Model
Introduction to text mining
Applications of Text Mining
Natural Language ToolKit Library
Text Extraction and Preprocessing: Tokenization
Text Extraction and Preprocessing: N-grams
Text Extraction and Preprocessing: Stop Word Removal
Text Extraction and Preprocessing: Stemming
Text Extraction and Preprocessing: Lemmatization
Text Extraction and Preprocessing: POS Tagging
Text Extraction and Preprocessing: Named Entity Recognition
NLP Process Workflow
If you're new to this technology, don't worry - the course covers the topics from the basics. If you've done some programming before, you should pick it up quickly.
If you’re a programmer looking to switch into an exciting new career track, this course will teach you the basic techniques used by real-world industry Machine Learning developers. These are topics any successful technologist absolutely needs to know about, so what are you waiting for? Enroll now!
Understand AI and Machine Learning in detail.
Understand Data Preprocessing.
Define Supervised Learning.
Describe Feature Engineering.
Identify the Classifications of Supervised Learning.
Define Unsupervised Learning.
Understand Time Series Modeling.
Describe Ensemble Learning.
Explain Recommender Systems.
Understand Text Mining.
No prerequisites are required, as the course covers the concepts from the scratch. However, basic knowledge of Python would help.
Check out the detailed breakdown of what’s inside the course
Use your certificate to make a career change or to advance in your current career.
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