Machine Learning

Industry  Ceritified Machine Learning Course

Course Description

At iSignal Academy, our ML program blends theory, projects, and mentorship to help you gain practical skills employers demand. You’ll master Python, Statistics, Algorithms, and ML frameworks—with step-by-step guidance from industry experts.

Machine Learning (ML) is the driving force behind today’s most innovative technologies—self-driving cars, voice assistants, recommendation systems, fraud detection, and more. As industries adopt AI and data-driven decision-making, the demand for skilled ML professionals is skyrocketing.

Course Overview

At iSignal Academy, our Machine Learning Certification Program is designed to transform beginners and IT professionals into industry-ready ML experts. This program combines theoretical foundations, hands-on coding, real-world projects, and expert mentorship to ensure you gain both knowledge and practical experience.

Machine Learning (ML) is the backbone of today’s AI revolution. From self-driving cars to personalized recommendations, ML is transforming every industry.

Build Your Programming Foundation.Secure Your IT Career.

• Machine Learning Engineer
• Data Scientist
• AI Engineer
• Research Scientist
• Business Intelligence (BI) Developer
• MLOps Engineer

 💰Course Fee: INR 14,999/- 🎉(Limited Time Offer: Flat 20% OFF for first 30 enrolments → 🔥INR 11,999/- only)

iSignal Academy Benefits

• 🔹 Hands-on Projects & Real-time Assignments
• 🔹 Expert Trainers & Industry Veterans
• 🔹 Affordable Fees with Flexible Learning Modes
• 🔹 Placement Assistance & Interview Preparation
• 🔹 Industry-Accredited Certification

📘 Course Detailed Content

Module 1: Introduction to Machine Learning

• What is ML? Importance & applications
• AI vs ML vs Deep Learning
• Types of ML: Supervised, Unsupervised, Reinforcement Learning
• Real-world ML use cases

Module 2: Python for Machine Learning

• Python fundamentals for ML
• Libraries: NumPy, Pandas, Matplotlib, Seaborn
• Data preprocessing & handling missing values
• Exploratory Data Analysis (EDA) with Python

Module 3: Statistics & Probability for ML

• Descriptive & Inferential Statistics
• Probability distributions
• Hypothesis testing & p-values
• Correlation & covariance

Module 4: Supervised Learning

• Regression: Linear & Logistic Regression
• Decision Trees & Random Forests
• K-Nearest Neighbors (KNN)
• Support Vector Machines (SVM)
• Evaluation metrics (Accuracy, Precision, Recall, F1-Score)

Module 5: Unsupervised Learning

• Clustering: K-Means, Hierarchical, DBSCAN
• Dimensionality Reduction: PCA, t-SNE
• Association Rule Learning (Apriori, Eclat)

Module 6: Feature Engineering & Model Optimization

• Feature scaling & transformation
• Handling categorical data
• Feature selection techniques
• Hyperparameter tuning (Grid Search, Random Search)
• Cross-validation

Module 7: Neural Networks & Deep Learning (Intro)

• Basics of Neural Networks
• Activation Functions
• Gradient Descent & Backpropagation
• Introduction to TensorFlow & Keras
• Building simple ANN models

Module 8: Advanced Machine Learning

• Ensemble Methods (Bagging, Boosting, XGBoost, AdaBoost)
• Time Series Forecasting (ARIMA, LSTM intro)
• Natural Language Processing (NLP Basics – Sentiment Analysis, Text Classification)
• Recommender Systems (Collaborative & Content-based filtering)

Module 9: Tools & Frameworks

• Python ML Libraries (Scikit-learn, TensorFlow, PyTorch)
• Data Visualization Tools (Matplotlib, Seaborn, Power BI basics)
• Jupyter Notebook, Google Colab

Module 10: Real-Time Projects

• Predicting House Prices (Regression)
• Customer Churn Prediction (Classification)
• Market Segmentation (Clustering)
• Sentiment Analysis on Tweets (NLP)
• Recommendation System for E-commerce

Module 11: Capstone Project & Industry Case Studies

• End-to-End ML Pipeline
• Deploying ML Model (Flask/Streamlit)
• Case Studies: Finance, Healthcare, E-commerce, Telecom

Module 12: Career Preparation & Mentorship

• Resume Building (ML Projects Focused)
• Portfolio on GitHub & Kaggle
• Mock Interviews & HR Preparation
• Career Roadmap: Data Analyst → ML Engineer → Data Scientist

🎯 Outcomes of This Course

After completing this program, you will be able to:
✔ Analyze & preprocess data for ML tasks
✔ Build and evaluate ML models
✔ Work with real-world datasets & industry projects
✔ Deploy ML models for business applications
✔ Apply for roles such as ML Engineer, Data Scientist, AI Specialist

📌 Industries Hiring in ML

High Demand

• ML is one of the fastest-growing fields in tech.
• Companies across IT, finance, healthcare, e-commerce, telecom, and automotive are actively hiring.

⭐ Features of Machine Learning (ML)

• Automation – Learns from data and reduces manual work.
• Self-Improvement – Improves accuracy with more data.
• Prediction Power – Forecasts outcomes and trends.
• Data Handling – Works with structured & unstructured data.
• Wide Applications – Used in healthcare, finance, e-commerce, telecom, etc.
• Scalability – Can handle big data and complex problem in ML & specialized roles)

🚀 Career Path in Machine Learning

Machine Learning opens doors to some of the most in-demand and high-paying careers in the tech industry. With the right skills, you can progress from beginner roles to advanced AI positions.

🔹 Average Salary Package in Machine learning

• Fresher / Junior (0–2 yrs): ₹6–10 LPA
• Mid-level (2–5 yrs): ₹12–20 LPA
• Senior / Specialist (5–10 yrs): ₹20–35 LPA
• Top / Leadership roles: ₹35 LPA and above (can go much higher in big tech

Course Highlights

• Duration: 6 Months (Instructor-led)
• Mode: Online + Offline (Classroom)
• Language: English
• Live Projects: 3 Real-time Projects
• Certification: Industry Recognized
• Career Support: Placement Guidance + Interview Preparation
• Learning Mode: Blendid Learning ( Online Live With Classroom)
• placement assistance upto 1year in Course

📲 Get a FREE Demo Session on Machine Learning – Just send “Hi” on WhatsApp 👉 7829450444

Interested in our Training? Fill out the enquiry form and our team will get back to you with details on fees, schedules, and offers.

Designation

Sreeram Bugude

Founder & CEO, Wireless RAN Head of Strategy – 5G,6G, with iSignal Research, Bangalore, with nearly 18Yrs+ experience in Wireless Domain worked in Nokia, Intel, Samsung, Mediatek, Infosys, L&T, and wireless startups, delivered multiple Wireless webinars, FDPs, Workshops in institutes like IIT Patna, IIITDM, Kurnool. Being IEEE ComSoc Member He had presented multiple 4G/5G Solutions in various International conferences like India Mobile Congress, New Delhi. Currently he is involved in Next Generation 5G/6G Air Interface Research and Development of Proof of Concepts, along with activities like career enablement, Trainings, LabSetups, Consulting

Research Focus:

mmwave, Beamforming, CSI-Reporting,massiveMIMO, OTFS, 6G, AI, ML for wireless RAN, Resource Allocations, SDR, GNU Radio, Python, C++ based Simulations for 6G

For more details please connect over linkedin Professional

 Network: https://www.linkedin.com/in/sreeram5g/