30 HOURS LIVE TRAINING
ENROLLMENT CLOSES IN
06
DAYS
:
10
HOURS
:
05
MINUTES
:
19
SECONDS
ADVANCED CERTIFICATION

MACHINE LEARNING
WITH AI

✓
100% Live Interactive Mentorship with Capstone Projects
✓
Industry-Recognized Certification & Career Placement Guidance
✓
Lifetime Access to LMS, Code Notebooks & Recording Library
Dr. Rupali N Randive
Led by Dr. Rupali N Randive PhD, M.Tech · 10+ Years Exp in Machine Learning & AI

Get started with ML & AI Course

Learn Today. Build Your Tomorrow · Reserve your seat

Practical Skills · Real-World Learning · Expert Guidance
TOOL STACK & ECOSYSTEM

Python 3

Core Programming

NumPy & Pandas

Data Prep & EDA

Scikit-Learn

Machine Learning

Matplotlib & Seaborn

Data Visualizations

Jupyter & VS Code

Interactive Notebooks

AI ML Co-Pilots

Gen AI for ML
STRUCTURED CURRICULUM

6 Comprehensive Units · 30 Hours Live Training (15 Days)

Click any unit to expand its detailed topics, practical focus, and hands-on ML implementation walkthroughs

01

AI & Machine Learning Fundamentals

Topics Covered:

  • Artificial Intelligence (AI), Machine Learning (ML), Deep Learning & Generative AI.
  • Supervised, Unsupervised, and Reinforcement Learning paradigms.
  • Core ML fundamentals: features, target, datasets, training, and testing.
  • Understanding the end-to-end Machine Learning lifecycle.
Focus:

Identifying ML problems, real-world applications and understanding an end-to-end ML problem.

02

Python, Data Handling, EDA & Data Preparation

Topics Covered:

  • Python programming fundamentals required for ML.
  • NumPy for fast numerical array computations.
  • Pandas for data manipulation, cleaning, and structured analysis.
  • Data cleaning: handling missing values, duplicates, and outliers.
  • Categorical data handling and encoding techniques.
Focus:

Feature selection, train/test split and preparing real-world datasets for ML models.

03

Regression

Topics Covered:

  • Supervised Learning principles and regression mechanics.
  • Linear Regression and Multiple Linear Regression.
  • Features, target variables, and generating numerical predictions.
  • Understanding prediction errors and residuals.
Focus:

Model training/testing and evaluation using MAE, RMSE and R², with applications such as house-price and sales prediction.

04

Classification

Topics Covered:

  • Logistic Regression fundamentals and decision boundaries.
  • Decision Trees & Random Forest ensemble learning.
  • K-Nearest Neighbours (KNN), Naive Bayes, and SVM overview.
  • Understanding algorithm selection for classification problems.
Focus:

Confusion Matrix, Accuracy, Precision, Recall, F1-score and comparing models using real-world classification problems.

05

Unsupervised Learning

Topics Covered:

  • Clustering fundamentals and hidden pattern discovery.
  • K-Means clustering algorithm & choosing optimal clusters.
  • Introduction to Hierarchical Clustering.
  • Pattern discovery and customer segmentation strategies.
Focus:

Introduction to Clustering, applications and limitations of unsupervised learning.

06

AI-Assisted ML & Final Project

Topics Covered:

  • Generative AI as an ML co-pilot for accelerated engineering.
  • AI-assisted Python coding, boilerplate generation, and debugging.
  • Using AI for rapid data exploration and visualization.
  • AI-assisted feature engineering and model understanding.
Focus:

AI-assisted interpretation, responsible AI usage, validation of AI outputs and an end-to-end ML project.

Suggested Real-World Capstone Projects:
• Customer Churn Prediction • House Price Prediction • Sales Prediction • Loan Risk Classification • Customer Segmentation • Spam Detection
PRACTICAL IMMERSION & OUTCOMES
Career-oriented & practical learning
Real-world datasets & business cases
Hands-on live exercises & demo projects
Build an interactive analytical dashboard
Guidance from industry professionals
Personal mentorship & portfolio review
FINAL OUTCOME

A Practical ML Foundation & End-to-End Predictive Portfolio Project

You will get a practical introduction to Machine Learning with AI, build end-to-end predictive models (such as Churn Prediction, House Price, Sales, Loan Risk, and Customer Segmentation), and develop a solid foundation for further learning, career transition, or AI/ML certifications.

OUR TRAINER

Learn From Industry Experts

Direct classroom instruction, live hands-on mentorship, and personalized guidance from leading practitioners

Dr. Rupali N Randive - Data Science & AI Trainer
Dr. Rupali N Randive
PhD, M.Tech · AI & Machine Learning Trainer
PhD, M.Tech & B.Tech · 10+ YEARS EXP

Meet Our Trainer
Dr. Rupali N Randive

Data Science Trainer

With 10+ years of academic, research, and industry experience, Rupali brings deep technical mastery and practical pedagogy into the classroom. Holding a PhD, M.Tech, and B.Tech, she is an expert in Data Science, Machine Learning, Python, Computer Vision, and Deep Learning.

Her core areas of specialization span modern AI and Data Science toolsets:

Data Science Machine Learning Python & NumPy Computer Vision Deep Learning AI ML Co-Pilots

All 30 hours are conducted as live training (15 days, 2 hours/day) at Mindlyft Ai complete with hands-on lab exercises and personalized dashboard review.

Training Format
30 Hours Live Training, taught in English with live practical lab exercises
Campus Location
2nd Floor, ABC Tiara, Opposite Akurdi Railway Station, Nigadi Pradhikaran, Pimpri-Chinchwad, Pune
Schedule & Mentorship
6 Modules · Real-world datasets & dedicated 1-on-1 guidance
STUDENT SUCCESS & REVIEWS

What Our Students Say About Us

R ★
Rohit Bhole
⋮
1 month ago

Physical campus at MindLyft AI provides a great environment for face-to-face mentorship and networking. Absolutely worth it for the hands-on project portfolio and community support you get. Highly recommended!

S ★
Sanket Khabiya
⋮
2 months ago

Mindlyft AI is a great place for anyone looking to explore and upskill in practical technology and data. The facility is well-organized, the environment is professional, and the team is knowledgeable and supportive.

O ★
Onkar Jadhav
⋮
3 months ago

One of the premier institutions to learn AI, Data science and all computer related courses at affordable prices. Also top notch infrastructure. The classrooms are very clean and tidy. The atmosphere gives a total professional feel of working in a corporate setup. Overall I recommend Mindlyft AI for all your IT up-skilling / re-skilling needs.

A ★
Anuja Gangan
⋮
3 weeks ago

Visited Mindlyft AI's institute in Pune and was genuinely impressed. The facility is well-equipped with modern systems, and the faculty is experienced, knowledgeable, and approachable.

OUR RECRUITING PARTNERS

Trusted by Leading Industry Leaders

Our students and alumni work across top tech enterprises, multinational corporations, and analytics consulting leaders

Wipro
Wipro
HCL Tech
HCL Tech
Tech Mahindra
Tech Mahindra
BMW
BMW
Mercedes
Mercedes
Audi
Audi
Infosys
Infosys
Deloitte
Deloitte
PwC
PwC
KPMG
KPMG
HSBC
HSBC
Citi
Citi
TCS
TCS
Mastercard
Mastercard
MUFG
MUFG
ANZ
ANZ
Federal Bank
Federal Bank
Johnson Controls
Johnson Controls
Fujitsu
Fujitsu
Invesco
Invesco
FactSet
FactSet
Interactive Brokers
Interactive Brokers
IIFL Finance
IIFL Finance
Motilal Oswal
Motilal Oswal
JM Financial
JM Financial
eClerx
eClerx
SS&C Technologies
SS&C Technologies
Acuity Knowledge Partners
Acuity Knowledge Partners
Clearwater Analytics
Clearwater Analytics
Capita
Capita
Wipro
Wipro
HCL Tech
HCL Tech
Tech Mahindra
Tech Mahindra
BMW
BMW
Mercedes
Mercedes
Audi
Audi
Infosys
Infosys
Deloitte
Deloitte
PwC
PwC
KPMG
KPMG
HSBC
HSBC
Citi
Citi
TCS
TCS
Mastercard
Mastercard
MUFG
MUFG
ANZ
ANZ
Federal Bank
Federal Bank
Johnson Controls
Johnson Controls
Fujitsu
Fujitsu
Invesco
Invesco
FactSet
FactSet
Interactive Brokers
Interactive Brokers
IIFL Finance
IIFL Finance
Motilal Oswal
Motilal Oswal
JM Financial
JM Financial
eClerx
eClerx
SS&C Technologies
SS&C Technologies
Acuity Knowledge Partners
Acuity Knowledge Partners
Clearwater Analytics
Clearwater Analytics
Capita
Capita
FAQS

Frequently Asked Questions

Everything you need to know about course sessions, materials, certifications, and attendance

1. What topics are covered in the Machine Learning with AI course?

The 30-hour course covers AI & Machine Learning fundamentals, data preparation with Python & NumPy, regression models, classification techniques, unsupervised learning (clustering & PCA), AI coding co-pilots for ML workflows, and an end-to-end hands-on capstone project.

2. Do I need prior coding or advanced AI experience to enroll?

No prior machine learning background is required. The curriculum begins from core fundamentals, explaining ML terminology, feature engineering, and data preparation step-by-step before progressing to advanced algorithms and AI tools.

3. What tools, libraries, and AI platforms will be taught?

You will work with Python, NumPy, Pandas, Scikit-Learn, Jupyter Notebooks, model evaluation libraries, and modern AI coding assistants / Co-Pilots to accelerate real-world ML workflows.

4. Who will be leading the classroom sessions?

The course is taught in person by Dr. Rupali N Randive (PhD, M.Tech & B.Tech · 10+ Years Experience), an expert in Data Science, Machine Learning, Python, Computer Vision & Deep Learning with extensive industry and academic expertise.

5. What is the batch schedule and campus location?

The program consists of 30 hours of live classroom training spread across 15 days (2 hours per day) at IIT Kanpur: IIT Kanpur Campus, Kalyanpur, Kanpur, Uttar Pradesh 208016.

6. Will I receive a certificate upon course completion?

Yes! Upon successful completion of all units and submission of your practical end-to-end Machine Learning project, you will receive an official Certificate of Completion from MindLyft AI.

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