Ready to start your journey in Machine Learning and build intelligent data-driven solutions?
This Machine Learning course is designed for students, working professionals and freshers
who want to learn how to analyze data, build predictive models and solve business problems using ML.
You’ll start from Python and math basics, then move into supervised, unsupervised and basic deep
learning concepts, along with real-world projects.
The program focuses on hands-on learning – using Jupyter Notebooks, popular ML libraries
and real datasets to build regression, classification and clustering models. By the end, you’ll be ready
for roles like Machine Learning Engineer (Junior), Data Analyst with ML skills, Applied ML Intern
or to move into advanced Deep Learning / AI specializations.
Python & Data Handling for ML
Math & Statistics for Machine Learning
Supervised & Unsupervised Learning Algorithms
Model Evaluation, Tuning & Deployment Basics
Industry-Oriented ML Projects & Case Studies
Fundamentals of Machine Learning, types of ML and understanding real-world use cases
Working with data in Python – NumPy, Pandas, cleaning, preprocessing & feature engineering
Core algorithms – Linear/Logistic Regression, Decision Trees, Random Forest, KNN, SVM (concepts + practice)
Unsupervised techniques – Clustering (K-Means, Hierarchical), Dimensionality Reduction (PCA) basics
Model evaluation – train/test split, cross-validation, confusion matrix, accuracy, precision, recall, F1-score, ROC-AUC (concepts + implementation)
Intro to basic Neural Networks & deployment concepts (saving models, using them in simple apps)
Machine Learning sits at the heart of AI, automation and data-driven decision making.
Companies across tech, finance, healthcare, e-commerce, telecom, marketing and more are
hiring people who can understand data and build ML models.
Learning ML gives you a strong competitive edge – whether you come from engineering, BCA, B.Sc,
B.Com, MBA or any other background. If you can convert data into insights and working models, you
can support better decisions, smarter products and automation.
At Skills Boost, our Machine Learning course is taught with a practical and
project-first approach. Trainers use real datasets (sales, marketing, finance, operations etc.) so
that you see how ML is used in industry.
Through live classes, hands-on notebooks, assignments and a final ML project, you’ll build
confidence to apply for junior ML, Data Analyst, Data & AI roles and take your career into
the world of AI.
After successfully completing this Machine Learning course, learners will be ready for ML-driven and data
problem-solving roles. Students can become…
