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Step into the world of AI with our in-depth Machine Learning course. Designed for beginners and upskillers alike, this program provides the tools, techniques, and hands-on projects you need to become an industry-ready Machine Learning and AI expert.
From your first algorithm to real-world AI solutions—gain expert-led training and hands-on experience to kickstart your ML/AI career with confidence.
Become a Machine Learning & AI Expert in Just 8 to 12 Months with Hands-On, Guided Training.
Master core Machine Learning and AI concepts from the ground up and build a solid foundation in data science—no prior experience required.
We have both online and offline interactive learning classes. Modules are divided into several parts consists of multiple lessons and tests
A valuable certificate will be awarded after completing the entire journey. The certificate will have a grading system
This course covers everything from the fundamentals of machine learning, including data preprocessing, model building, and algorithm selection, to advanced topics like NLP, clustering, and recommendation systems.
You’ll learn to build efficient, real-world ML models, solve data-driven problems, and gain a solid foundation to advance in data science, AI, or analytics roles.
Understand ML types, workflows, and set up your environment using Python, Jupyter, NumPy, and Pandas.
Analyze, clean, and transform data using Pandas and NumPy, handling outliers, missing values, and feature engineering.
Create insightful visualizations using Matplotlib, Seaborn to interpret patterns and trends.
Learn regression and classification techniques like Linear, Logistic, Decision Trees, and Random Forest.
Master SVM, KNN, and Naive Bayes for building and evaluating high-performance predictive models.
Improve model performance with AdaBoost, XGBoost, and handle class imbalances using modern techniques.
Explore clustering with K-means, DBSCAN, and simplify data using PCA.
Build NLP and recommendation systems, and use Scikit-learn for model building, tuning, and validation.
Used in: Entire course
The foundational programming language for building ML models, handling data, and deploying solutions.
Used in: All practical sessions
An interactive IDE for writing, running, and documenting Python code in real time.
Used in: Data preprocessing and statistical analysis
Enables high-speed mathematical computations and array handling.
Used in: Data manipulation and EDA
Simplifies working with structured data, cleaning, filtering, and transforming datasets.
Used in: Data visualization
Used to create static and advanced visualizations like bar charts, heatmaps, and scatter plots.
Used in: Interactive data visualization
Helps create dynamic, interactive charts and dashboards for exploratory data analysis.
Used in: Model training, evaluation, tuning
Supports algorithms like regression, classification, clustering, and dimensionality reduction.
Used in: Web scraping
Extracts structured data from websites for ML datasets and analysis.
Used in: Advanced model building
A deep learning framework used for building and training custom neural networks and deploying machine learning models.
Used in: NLP modules
Used for text processing tasks like tokenization, stemming, and sentiment analysis in basic NLP projects.
Used in: Deep learning
Simplifies building and training neural networks using a beginner-friendly interface over TensorFlow.
Used in: Statistical analysis and model optimization
A scientific computing library that extends NumPy with advanced functions for optimization, integration, interpolation, linear algebra, and statistical analysis—crucial for ML model evaluation and tuning.
Hear directly from our students as they share their experiences, success stories, and how our practical training transformed their careers.
Upon successful completion of the course, you will receive a certificate which will enable you to -
Explore answers to common queries about course content, tools covered, career opportunities, learning formats, and certification to help you make an informed decision.
ML is at the heart of AI revolutionizing industries like healthcare, finance, retail, and automation. With rising demand for intelligent systems, skilled ML professionals are in high demand globally.
AI tools can automate basic workflows, but building, training, and deploying intelligent systems still require human insight. This course teaches you to work with AI—not be replaced by it.
Basic programming helps, but we start from the ground up. Python essentials and ML basics are covered thoroughly.
Our course emphasizes practical, real-world coding, not just theory. You’ll write and debug programs in every class to build confidence and real programming skills.
Yes, we provide doubt-solving sessions, one-on-one guidance, and continuous support to help you at every step of your learning journey.
Absolutely. If you're willing to learn, we simplify even complex topics with real examples and step-by-step guidance.
Upon successful completion of the course, you will receive a certificate which will enable you to -
