Data Science and Analytics Course with AI - Master Diploma

Become a Leader with Our Master's in Data Science and Analytics Course with AI

Elevate your expertise with our Masters in Data Science and Analytics Course with AI. This comprehensive program covers advanced data analysis, machine learning, and AI, equipping you for leadership roles in the data science field with real-world projects and expert instruction.

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All Levels
36 Weeks
MIT Certification
Industry Immersion
Capstone Projects

Overview

Our Master’s program extensively studies data analysis, machine learning, and artificial intelligence. Focusing on practical applications and real-world case studies, you’ll gain the advanced skills needed for leadership roles with our data science and analytics course.

Data Scientist
Machine Learning Engineer
Data Analyst
AI Specialist
Data Engineer
Business Analyst

Targeted Job
Roles

Training and Methodology

By enrolling in this course, you will gain access to -

Hands-On Projects - Analyze real datasets with Python, SQL, Power BI.
Industry Collaboration - Solve case studies with top data-driven companies.
Capstone Projects - Build AI-powered solutions for business challenges.
Evaluation - Track progress with assignments and project reviews.

Why Choose This
Course?

Lead with Advanced Skills in Data Science and Analytics with AI

Our Master’s in Data Science and Analytics Course equips you with the advanced skills and knowledge needed for leadership in data science and Analytics with AI. With practical experience and expert instruction, you’ll be prepared to excel in high-impact roles and drive innovation in the field.

100% Job Placement Guarantee

Job placement Guarantee readiness.
Real time projects

Work on industry-relevant projects to apply your skills.
Reviews and feedback

Regular reviews to ensure your progress and success.

Skills acquired from this course

Advanced data analysis and visualization techniques
Expertise in machine learning and AI algorithms
Proficiency in handling and analyzing large datasets
Leadership skills for managing data projects and teams

Tools & Languages Included In This course

The Course Syllabus

The course covers important topics.

Advanced Data Analysis
- Data Cleaning and Preparation
- Statistical Analysis and Interpretation
Python with Data Science
- Python with Data Science
Machine Learning
- Introduction to Machine Learning
  - What is Machine Learning
  - Applications of Machine Learning
  - Supervised Vs Unsupervised Machine Learning
  - Regression vs classification
- Exploratory Data Analysis (EDA)
  - Finding null values
  - Detecting and removal of outliers
  - Feature scaling – : Standardization and normalization
- Introduction to Linear Regression
  - What is regression?
  - What is linear regression?
  - Building First ML model for marks prediction
  - Simple linear regression
  - Multiple Regression
  - Polynomial Regression
  - Error functions in Regression (MAE, MSE, RMSE)
  - Calculating accuracy using R2Score
- CASE STUDY -: Car Price Prediction on cars24 dataset
- Introduction to Overfitting and underfitting
  - Overfitting Vs underfitting
  - Bias-Variance Tradeoff
  - Regularization Techniques -: Ridge and Lasso
  - Understanding and demonstrating Ridge and lasso regression techniques
  - Cross Validation Techniques
- Introduction to Logistic Regression
  - Sigmoid function
  - Understanding parameters of logistic regression
  - ROC AUC Curve
  - Confusion Matrix -: Precision, Recall, accuracy, f1 Score
- Introduction to KNN
  - Understanding working of K – Nearest Neighbors
  - Advantages and drawbacks of using KNN
  - KNN for regression
- Introduction to SVM
  - Understanding Support Vector Machine
  - Hard and soft margin
  - Understanding Support Vectors , Hyperplane
  - Kernel technique
  - SVM for regression
- Naive Bayes Classifier
  - Understanding Naive Bayes Theorem
  - Introduction to text classification
  - NLP pipeline
  - Vectorization of text data
  - Case Study -: Spam mail classification using naive bayes
  - Understanding Support Vector Machine
  - Hard and soft margin
  - Understanding Support Vectors, Hyperplane
  - Kernel technique
  - SVM for regression
- Decision Tree classifier
  - Working of DT
  - Gini Index and Entropy
  - Pruning techniques
  - Advantages and disadvantages of Decision Tree
  - Decision Tree for regression
- Introduction to Ensemble learning
  - What is Bagging?
  - Random Forest Classifier
  - ADA Boost, XGboost, Gradient Boost
- Unsupervised Machine Learning Algorithm
- Project deployment using Flask Framework
  - Clustering
  - K-means Clustering
  - Hierarchical clustering
  - Association rules
  - PCA (principle component analysis)
- CASE STUDY ON BREAST CANCER DETECTION USING CLASSIFICATION ALGORITHMS
- CASE STUDY ON FRAUD DETECTION USING CLASSIFICATION ALGORITHMS
Artificial Intelligence
- Neural Networks and Deep Learning
- AI Techniques and Applications
- Natural Language Processing (NLP)
- Computer Vision
Data Visualization and BI Tools
- Advanced Visualization Techniques
- Tableau
  - Tableau Architecture and Features
  - Data Visualization Techniques
  - Dashboard Design and Interactivity
- Power BI
  - Introduction to Power BI Tools
  - Data Preparation and Visualization
  - DAX Queries and Report Creation
- Advance Excel
Capstone Projects
- Industry-Relevant Data Science Projects
- Real-World AI and Machine Learning Applications

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excellence?

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Certification For This
Course

Receive a recognized certification upon course completion, validating your skills and boosting your career prospects.

MIT Certification - Master's in Data Science and Analytics Course

Capstone Projects In
This Coursework

Our projects are directly aligned with the coursework, ensuring practical application of what you learn. This hands-on approach deepens your understanding and prepares you for real-world challenges.

Superstore Data Analysis Dashboard

This project involves creating an interactive dashboard using Power BI to analyze sales data from a superstore.

Random Password Generator

This mini project creates a secure password generator that can generate passwords of varying lengths and complexities.

Vehicle Price Prediction

In this project, machine learning techniques are used to forecast vehicle prices based on attributes like make, model, year, mileage, and condition.

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Frequently Asked Questions

Find answers to all your questions about our diverse course categories. Discover the range of subjects we offer, and learn how to choose the right courses to match your interests and career goals. Let us guide you in navigating our extensive catalog to find the perfect fit for your educational journey.

Who can enroll for this course?

Any person with ME, MTech, BE, BTech, BCA, MCA, Msc, Bsc in Computer Science, Bsc IT, Msc IT, Diploma, IT, AI, ML can register for this course.
What will be the mode of delivery?

We offer 3 delivery models
1) Classroom
2) Live Online
3) Recorded lectures
Kindly contact us with your requirements.
Will I receive a certificate after completion of this course?

Yes, you will be getting a certificate from Milestone Institute of Technology.
Does this course align with Industry requirements?

Yes, at MIT we ensure our syllabus and exercises are up to date as per industry requirements. We have used industry examples wherever possible in the course material. Additionally, you can also register your interest in Industry internships opportunities with our placement department.

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