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Enroll in Machine Learning Course โ Master 8 ML Algorithms with Python!
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Machine Learning
Python
8 Algorithms
65 Lessons
Machine Learning
Course Online with
8 ML Algorithms โ
Master Machine Learning from scratch with EasyShiksha's ultimate course. Learn Python, NumPy, Pandas, Matplotlib, and 8 complete ML algorithms โ from Linear Regression to Random Forest โ with a globally recognized certificate.
No prior ML experience needed
8 complete ML algorithms
Python + NumPy + Pandas + Matplotlib
Internship certificate available
Model Trained!Ankit's Random Forest: 94.6% accuracy
8 Machine Learning Algorithms
Linear RegressionSupervised
Logistic RegressionClassification
SVMClassification
KNNSupervised
K-MeansUnsupervised
Naive BayesProbabilistic
Decision TreeClassification
Random ForestEnsemble
Model Accuracy Comparison
Certificate Included+ Internship certificate available
24,000+
Students Enrolled
8
ML Algorithms Taught
65
Video Lessons
4.8/5
Average Rating
8 Machine Learning Algorithms
Every Core ML Algorithm โ Taught from Scratch
From simple regression to powerful ensemble methods โ this machine learning course teaches you every major algorithm category, with theory and practical implementation in Python.
01
Linear Regression
SupervisedPredict continuous values by fitting a line to data. Learn the maths behind regression, cost functions, and gradient descent.
02
Logistic Regression
ClassificationClassify binary outcomes using the sigmoid function. Master probability outputs, decision boundaries, and model evaluation.
03
Support Vector Machine
ClassificationFind optimal hyperplanes that maximally separate classes. Learn support vectors, kernels, and margin maximization.
04
K-Nearest Neighbours
SupervisedClassify data points based on the K closest neighbours. Understand distance metrics, feature scaling, and parameter tuning.
05
K-Means Clustering
UnsupervisedGroup unlabelled data into K clusters. Learn centroid initialization, convergence, and the elbow method for K selection.
06
Naive Bayes
ProbabilisticApply Bayes' theorem for fast, effective classification. Ideal for text classification, spam filtering, and categorical data.
07
Decision Tree
ClassificationBuild interpretable tree-based models using information gain and Gini impurity. Understand pruning and overfitting prevention.
08
Random Forest
EnsembleCombine hundreds of decision trees for powerful ensemble predictions. The most versatile and widely used ML algorithm in production.
Full Curriculum
Machine Learning Course โ 65 Lessons
A complete Python-to-ML curriculum. Start with 2 free preview lessons โ unlock 63 more lessons and internship access with enrollment.
Free Preview Lessons โ 2 Lessons Included
1Introduction To Course
Free
2Python Complete Course Introduction
Free
Free Preview Ends Here
Go to Class Room
Unlock 63 More Lessons + Internship Access
Full course + real internship experience โ affordable one-time access Python Programming โ 29 Classes
3Python Class 1 : Introduction To Python
4Python Class 2 : Setting Python Environment
5Python Class 3 : Introduction To Variables
6Python Class 4 : Introduction To Keywords
7Python Class 5 : Introduction To Datatypes
8Python Class 6 : ID Function
9Python Class 7 : Arithmetic Operator
10Python Class 8 : Logical Operator
11Python Class 9 : Comparison Operator
12Python Class 10 : Bitwise Operator
13Python Class 11 : Membership Operator
14Python Class 12 : Identity Operator
15Python Class 13 : Conditional Statements
16Python Class 14 : For Loop and Range Function
17Python Class 15 : While Loops
18Python Class 16 : Break and Continue
19Python Class 17 : Function
20Python Class 18 : Try Except Finally Blocks
21Python Class 19 : String and Functions
22Python Class 20 : List and Functions
23Python Class 21 : Tuple and Functions
24Python Class 22 : Dictionary and Functions
25Python Class 23 : Class and Object
26Python Class 24 : Class Methods
27Python Class 25 : Inheritance and Its Types
28Python Class 26 : Polymorphism and Its Types
29Python Class 27 : Encapsulation and Access Modifiers
30Python Class 28 : Abstraction
31Python Class 29 : Mini Project
Data Science Introduction
32Complete Data Science Course
NumPy โ Numerical Computing
33Numpy Complete Course
34Numpy Class 1 : Import and Install
35Numpy Class 2 : Array and Its Types
36Numpy Class 3 : Datatypes
37Numpy Class 4 : NDIM Function
38Numpy Class 5 : ARANGE Function
39Numpy Class 6 : CONCATENATE Function
40Numpy Class 7 : NDMIN Function
41Numpy Class 8 : NDITER Function
42Numpy Class 9 : All Functions
Pandas โ Data Manipulation
43Pandas Class 1 : Import Dataset
44Pandas Class 2 : Head & Tail Function
45Pandas Class 3 : Info Function
46Pandas Class 4 : Drop NA Function
47Pandas Class 5 : Fill NA Function
48Pandas Class 6 : Drop Duplicates Function
49Pandas Class 7 : Replace Values Function
Matplotlib โ Data Visualization
50Matplotlib Class 1 : Import Dataset
51Matplotlib Class 2 : Show Function
52Matplotlib Class 3 : Marker Function
53Matplotlib Class 4 : Xlabel Ylabel Function
54Matplotlib Class 5 : Title Function
55Matplotlib Class 6 : Linestyle Linewidth Function
56Matplotlib Class 7 : Barplot
Machine Learning โ 8 Algorithms (The Core of This Course)
57Complete Machine Learning Introduction
58Machine Learning Class 1 : Linear Regression
59Machine Learning Class 2 : Logistic Regression
60Machine Learning Class 3 : Support Vector Machine
61Machine Learning Class 4 : KNN
62Machine Learning Class 5 : K Means Clustering
63Machine Learning Class 6 : Naive Bayes
64Machine Learning Class 7 : Decision Tree Classifier
65Machine Learning Class 8 : Random Forest
Ready to master Machine Learning & all 8 ML algorithms?
Enroll Now โ Get Full Access
Enroll once โ get all 65 lessons, lifetime access, certificate & internship option.
Skills You Will Gain
What You Get From This Machine Learning Course
From Python basics to deploying real ML models โ every technical skill an aspiring machine learning engineer needs.
Python for Machine Learning
Master Python in 29 dedicated classes โ variables, all operators, control flow, loops, functions, OOP (classes, inheritance, polymorphism, encapsulation, abstraction) โ the essential programming foundation for ML.
8 Core ML Algorithms
Implement and understand all 8 algorithms: Linear Regression, Logistic Regression, SVM, KNN, K-Means Clustering, Naive Bayes, Decision Tree, and Random Forest โ covering regression, classification, and clustering.
Data Wrangling with Pandas
Prepare real datasets for ML โ import data, explore with head/tail/info, handle missing values, remove duplicates, and replace values. Clean data is the foundation of accurate ML models.
Data Visualization with Matplotlib
Visualize datasets and model results with Matplotlib โ bar plots, line charts, marker customization, axis labels, and chart titles. See your data before building your ML model.
NumPy for ML Mathematics
Perform fast numerical computations with NumPy arrays โ the mathematical backbone of every ML algorithm. Master NDIM, ARANGE, CONCATENATE, NDITER, and all core NumPy functions.
Recognized Certificate & ML Career
Earn a globally recognized ML course certificate โ accepted by universities and employers worldwide. LinkedIn-ready with a verifiable ID. A powerful credential for ML Engineer, Data Scientist, and AI Developer roles.
Machine Learning
Python
Data Science & Machine Learning โ Ultimate Course for All
The ultimate machine learning course โ Python (29 classes including full OOP), NumPy, Pandas, Matplotlib, and 8 complete ML algorithms from Linear Regression to Random Forest. Build real projects and earn a recognized certificate.
Enroll in Machine Learning Course Now
Why This ML Course
Start Machine Learning Course Today
The Ultimate Machine Learning Course โ Python to Random Forest
EasyShiksha's machine learning course is trusted by 24,000+ students and rated 4.8/5. The only ML course that takes you from Python zero to all 8 core ML algorithms โ with a recognized certificate and optional internship credential.
Zero to ML EngineerStarts from Python Class 1 โ no prior machine learning or programming knowledge required
All 8 Core ML AlgorithmsLinear Regression โ Logistic Regression โ SVM โ KNN โ K-Means โ Naive Bayes โ Decision Tree โ Random Forest
Recognized CertificateGlobally accepted ML certificate for universities, employers, and government applications โ LinkedIn shareable
Dual Certificate OptionEnroll with internship to earn ML course certificate + internship certificate from one enrollment
Your ML Certificate
Enroll & Get ML Certificate
Earn a Machine Learning Certificate That Employers Recognize
Completing EasyShiksha's machine learning course earns you a globally recognized digital certificate โ accepted by universities, valued by tech employers worldwide, and shareable on LinkedIn with a unique verifiable ID.
Globally Recognized ML CertificateAccepted by universities, employers, and government bodies worldwide
Unique Verifiable Certificate IDEmployers can authenticate your ML certificate instantly with a live verification link
Internship Certificate AvailableEnroll with internship to earn both ML course + internship certificate from one enrollment
LinkedIn & Resume ReadyAdd to LinkedIn under Licences & Certifications with a live verification link
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Student Reviews
What Machine Learning Students Are Saying
24,000+ students enrolled. Real reviews from people who completed the machine learning course online on EasyShiksha.
ML Certified
I went from zero programming knowledge to implementing Random Forest and SVM in Python. The 29 Python classes are incredibly thorough โ especially the OOP section. After completing this machine learning course, I got shortlisted for an ML Engineer role at a fintech startup within 6 weeks!
ML Certified
The decision tree and random forest sections are genuinely excellent โ better than what I found in most other online ML courses. The way NumPy and Pandas are taught as prerequisites to the ML algorithms makes the theory completely practical. The certificate is well-recognized by employers.
ML Certified
I enrolled in the machine learning course with the internship bundle. Having both the ML course certificate and the internship certificate on my LinkedIn made an immediate difference โ got noticed by a recruiter who specifically mentioned the EasyShiksha ML certification. Highly recommended!
ML Course FAQs
Frequently Asked Questions
Everything you need to know before enrolling in EasyShiksha's machine learning course online.
What machine learning algorithms are taught in this course?
EasyShiksha's machine learning course online teaches 8 complete ML algorithms: Linear Regression, Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbours (KNN), K-Means Clustering, Naive Bayes, Decision Tree Classifier, and Random Forest โ covering supervised, unsupervised, and ensemble learning methods.
Is this machine learning course suitable for beginners?
Yes. EasyShiksha's machine learning course online starts from Python Class 1 โ an introduction to Python itself. No prior programming, mathematics, or machine learning knowledge is required. The course builds systematically from Python basics through data tools (NumPy, Pandas, Matplotlib) to all 8 ML algorithms.
Does this machine learning course include Python programming?
Yes. This machine learning course includes 29 dedicated Python classes โ covering variables, keywords, data types, all six operator categories, conditional statements, loops, functions, exception handling, strings, lists, tuples, dictionaries, and full OOP including classes, inheritance, polymorphism, encapsulation, abstraction, and a mini project.
What is the difference between supervised and unsupervised ML โ does this course cover both?
Yes. This machine learning course online covers both paradigms: Supervised learning (Linear Regression, Logistic Regression, SVM, KNN, Naive Bayes, Decision Tree, Random Forest) where models learn from labelled data, and Unsupervised learning (K-Means Clustering) where models find patterns in unlabelled data โ giving you a complete ML foundation.
What certificate will I get after the machine learning course?
Upon completing EasyShiksha's machine learning course online, you receive a globally recognized digital certificate of completion โ accepted by universities for academic credit, valued by tech employers worldwide, and shareable on LinkedIn with a unique verifiable ID that recruiters can instantly authenticate.
How long does the machine learning course take to complete?
The machine learning course online has 65 lessons and can typically be completed in 8 to 12 weeks at a comfortable pace. It is fully self-paced with lifetime access โ learn at your own schedule and earn your certificate when you are ready.
What jobs can I get after completing the machine learning course?
Completing EasyShiksha's machine learning course online qualifies you for roles including Machine Learning Engineer, Data Scientist, AI Developer, Data Analyst, Python Developer (ML focus), and Business Intelligence Analyst โ all among the highest-paying and fastest-growing tech careers globally.
Does the machine learning course include an internship certificate?
Yes. EasyShiksha's machine learning course can be enrolled with an internship program, giving you both a course completion certificate and an internship certificate from one enrollment โ two recognized credentials that significantly strengthen your ML resume and LinkedIn profile.
Why Take a Machine Learning Course Online in
Machine Learning is the engine powering the most transformative technologies of the decade โ recommendation systems, fraud detection, medical diagnosis, autonomous vehicles, and natural language processing. In , ML engineers and data scientists remain among the most in-demand and highest-compensated professionals in the tech industry. Taking a machine learning course online is the most efficient path to entering this field โ and Python is the language that makes it accessible to everyone.
Why Learning All 8 ML Algorithms Matters
Many introductory courses teach one or two algorithms โ but real ML engineers need to choose the right algorithm for each problem. Should you use Linear Regression or Random Forest? Is this a KNN problem or an SVM problem? Is the data labelled (supervised) or unlabelled (K-Means)? EasyShiksha's machine learning course online teaches all 8 core algorithms โ giving you the comparative knowledge to make the right choice for any ML task.
The course takes you through the complete ML workflow: prepare data with Pandas, perform numerical operations with NumPy, visualize your dataset with Matplotlib, select your algorithm, train your model, and evaluate performance. By the end, you have hands-on experience with every major algorithm category โ regression, classification, clustering, and ensemble methods โ implemented in Python.
Who Should Take This Machine Learning Course Online?
This machine learning course online is ideal for students and graduates from any stream looking to enter the AI/ML field, software developers wanting to add ML to their skill set, data analysts seeking to transition into machine learning roles, scientists and researchers applying ML to their domain, and entrepreneurs building data-driven products. Python Class 1 is literally the starting point โ no prior experience of any kind is required.
Machine Learning Course Online
Python Machine Learning
ML Course with Certificate
ML Algorithms Course
Random Forest & SVM Course
NumPy Pandas ML Course
With 24,000+ enrollments, a 4.8/5 rating, and a globally recognized certificate, EasyShiksha's machine learning course online is the trusted choice for learners worldwide who want to master Python, implement all 8 ML algorithms, and launch a career in machine learning and AI. Enroll today and start building models that learn.
// Machine Learning Course Online
Master Machine Learning โ All 8 Algorithms with Python
Join 24,000+ students on EasyShiksha's machine learning course. Learn Python, NumPy, Pandas, Matplotlib & implement 8 complete ML algorithms โ earn your certificate and launch your ML career.
// ML_ALGORITHMS = 8 | PYTHON = included | CERTIFICATE = recognized | INTERNSHIP = available
