Predictive Edge – Data Science and ML Simplified (with Placement Assistance)
About Course
🚀 Course Overview
Predictive Edge is a comprehensive 11-month Data Science and Machine Learning program designed by IteraLearn Solutions Private Limited. This course simplifies the complexities of Data Science and ML, making it accessible for beginners while also enriching professionals who want to upskill. Through structured learning, real-world projects, and personalized mentorship, you will gain the skills to analyze data, build predictive models, and deploy intelligent solutions that create real impact.
The course follows a step-by-step roadmap (from Python basics to advanced ML, Deep Learning, and NLP) ensuring learners build a solid foundation first, then advance to industry-level expertise. By the end, you will have a portfolio of projects, interview readiness, and the confidence to step into Data Science roles across industries.
🏆 Key Highlights
-
Duration: 11 Months (Online – Live + Recorded Access)
-
Mode: Instructor-led with guided mentorship
-
Level: Beginner to Advanced (no prior coding experience required)
-
Projects: 6+ mini-projects + 1 Capstone Project
-
Certification: Industry-recognized Certificate from IteraLearn Solutions
-
Career Support: Resume Building, Mock Interviews, Job Preparation
📚 Course Structure
Month 1 – Basic Python
-
Python syntax, data types, loops, functions
-
Jupyter Notebook, GitHub basics
-
Hands-on: Writing Python programs
Month 2 – Statistics & Probability
-
Descriptive & Inferential Statistics
-
Probability distributions, hypothesis testing
-
Hands-on: Statistical analysis using Python
Month 3 – Advanced Python + SQL
-
Object-Oriented Programming, error handling
-
Libraries: NumPy, Pandas
-
SQL for Data Science (queries, joins, aggregation)
-
Hands-on: Database-driven analysis
Month 4 – Data Visualization
-
Matplotlib, Seaborn, Plotly
-
Dashboarding with Power BI / Tableau
-
Hands-on: Business insights visualization
Month 5 – Machine Learning (Core)
-
Supervised Learning (Regression, Classification)
-
Unsupervised Learning (Clustering, Dimensionality Reduction)
-
Model evaluation and tuning
-
Hands-on: Building ML models for real-world datasets
Month 6 – Data Manipulation
-
Data Cleaning, Feature Engineering, Handling Missing Data
-
Advanced Pandas techniques
-
Hands-on: Preparing raw datasets for ML
Month 7 – Deployment & Cloud Basics
-
Model deployment with Flask/Django
-
API integration, Docker basics
-
Introduction to AWS/GCP cloud deployment
-
Hands-on: Deploying ML model as a web service
Month 8 – Deep Learning
-
Neural Networks basics
-
TensorFlow & PyTorch
-
Image recognition, ANN, CNN, RNN
-
Hands-on: Handwritten digit classification
Month 9 – NLP & Computer Vision
-
Natural Language Processing (Text preprocessing, Sentiment analysis)
-
Transformers & BERT basics
-
Intro to Computer Vision (image classification, object detection)
-
Hands-on: Chatbot project / Text classification
Month 10 – Career Preparation
-
Resume building & GitHub portfolio optimization
-
Communication skills for Data Science
-
Mock interviews & case studies
-
Hands-on: End-to-end ML project presentation
Month 11 – Capstone Project & Industry Readiness
-
Work on a real-world, end-to-end project
-
Solve a predictive analytics / ML problem from scratch
-
Final project presentation to mentors
-
Certification + Job readiness support
🎯 Who Should Enroll?
-
Students looking to start a career in Data Science
-
Working professionals aiming to upskill or transition to ML roles
-
Entrepreneurs & freelancers interested in AI-driven solutions
-
Anyone curious about data, AI, and predictive modeling
🔑 Career Opportunities After Course
-
Data Scientist
-
Machine Learning Engineer
-
Business/Data Analyst
-
NLP Engineer
-
AI Research Assistant
🌟 Why Choose Predictive Edge?
-
Structured 11-month roadmap (from basics to advanced)
-
Hands-on learning with real datasets
-
Expert mentors with industry experience
-
Resume & interview preparation included
-
Placement assistance & networking opportunities
👉 At the end of this course, you won’t just know Data Science — you’ll have the “Predictive Edge” to stand out in the job market.
Course Content
Basic Python
-
Introduction to Python & Setup
-
Variables, Data Types & Operators
-
Input and Output in Python
-
Strings – Basics and Manipulation
-
Lists – Basics, Indexing and Slicing
-
Tuples and Sets
-
Dictionaries – Keys & Values
-
Conditional Statements (if-else)
-
Loops – (For Loops, While Loops, Nested Loops)
-
Functions – Defining and Calling
-
Modules and Packages
-
Error Handling Basics
