CognivaRise

Building Your Future...

Career-focused technology program

Machine Learning

Machine Learning (ML) enables systems to learn from data and make intelligent decisions without explicit programming. At CognivaRise, our Machine Learning program is designed to build strong foundations and practical skills required to solve real-world problems using data-driven models.

  • Lifetime learning access
  • 3+ practical projects
  • Expert mentor guidance
  • Live doubt-clearing support
  • Internship certificate
  • Placement preparation
  • 60-day learning path
  • Regular evaluation
Program overview

Build knowledge you can apply

Boost your career with our Machine Learning program developed in collaboration with IITs and industry partners. The program includes exclusive learning modules, hands-on projects, and placement assistance to prepare you for high-demand roles.

Learn core concepts such as Python, NumPy, Pandas, Supervised & Unsupervised Learning, Regression, Classification, and Model Evaluation through self-paced videos, guided modules, and real-world projects.

Machine Learning learning overview
Structured learning path

Curriculum built for practical progress

Move from core concepts to hands-on work with guided modules and portfolio-focused projects.

Industrial Training

Module 1 Introduction to Python and variable
Module 2 Features of Python
Module 3 How to download and install Python
Module 4 Python Variables
Module 5 Introduction to Machine Learning
Module 6 AI vs ML vs Deep Learning
Module 7 Self driving car
Module 8 Types of Machine Learning
Module 9 Introduction to Supervised Machine Learning
Module 10 Types of Supervised Machine Learning
Module 11 KNN algorithm
Module 12 Logic in the Algorithm
Module 13 KNN Algorithm in Excel
Module 14 Linear Regression
Module 15 Neural network – Introduction and functioning
Module 16 Functioning of Neural networks
Module 17 Training Neural network
Module 18 Bias and variance
Module 19 Fitting in Machine Learning
Module 20 Unsupervised Machine Learning
Module 21 K-means clustering
Module 22 Reinforcement learning
Quiz

Advanced Internship Projects

Project 1 Predict Diabetes
Project 2 Fraudulent Transaction
Project 3 Predicting the survival chances in a accident
Project 4 Second Hand Car Price Prediction
Project 5 Music Genre Classification

Program credentials

Certificates that recognise your progress

Certificate eligibility depends on the selected plan and successful completion of the applicable learning requirements.

  • Participation Certificate
  • Industrial Training Completion Certificate
  • Internship Completion Certificate
Participation certificate sample
Industrial training certificate sample
Internship certificate sample
Meet your guides

Learn with experienced mentors

Get practical guidance from professionals who connect concepts with real-world application.

Abhishek Pitale

Abhishek Pitale

Company associated with Abhishek Pitale

With professional experience at Lloyds, Abhishek has expertise in Machine Learning, predictive analytics, and data-driven solutions. He is passionate about mentoring aspiring ML engineers through practical projects and real-world industry applications.

Dippak Ambhure

Dippak Ambhure

Company associated with Dippak Ambhure

Deepak is an AI Professional at Oracle, specializing in Machine Learning, Data Science, and intelligent systems. With hands-on industry experience, he mentors students in building real-world ML models and solving complex business problems using data.

Choose how you learn

Simple learning plans for different goals

Compare the core support included in each plan. Our advisor can confirm current availability and complete inclusions before payment.

Self-Paced Learning

For independent learners who want maximum flexibility.

6,000/ course
  • Lifetime dashboard access
  • Self-paced learning modules
  • 3+ industry-based projects
  • Completion certificates
  • Interview and résumé preparation
  • Student community access

Professional

For comprehensive technical and career preparation.

15,000/ course
  • Everything in Personal Mentorship
  • Aptitude and soft-skill grooming
  • Group discussion preparation
  • Extended mock interviews
  • Hiring-readiness guidance
  • Partner opportunities when eligible
Learner experiences

What students say about CognivaRise

Feedback from learners who developed practical skills through structured training and mentorship.

★★★★★
“CognivaRise gave me the tools and mentorship to stand out. It has been a turning point in my learning journey.”
Sonali PatilCognivaRise learner
★★★★★
“CognivaRise helped me build skills that employers value. The practical guidance gave me greater confidence in my career preparation.”
Rushi PisoleCognivaRise learner
★★★★★
“The program helped me build industry-relevant skills step by step. I now feel more confident approaching practical challenges.”
Mayuri PatilCognivaRise learner
★★★★★
“The learning experience strengthened my critical thinking and problem-solving approach through practical exercises and projects.”
Shravani ChitnisCognivaRise learner
★★★★★
“CognivaRise offered a useful balance of concepts and practical work that helped me prepare for long-term professional growth.”
Kaustubh PatilCognivaRise learner
★★★★★
“I learned how to connect concepts with practical work. The combination of guidance and projects made a real difference.”
Pranali GovandeCognivaRise learner
★★★★★
“The structured learning path helped me understand what to practise and how to apply my skills toward my career goals.”
Kunal MehtaCognivaRise learner
Common questions

Frequently asked questions

Clear answers to help you make an informed enrolment decision.

Free program guidance

Take the next step in Machine Learning

Tell us about your learning goal. Our team will explain the current schedule, plan options and enrolment process.

  • No payment required to request guidance
  • Clear information about batch availability
  • Recommendations based on your goal
Ready when you are

Build your learning plan with CognivaRise

Review the curriculum or speak with an advisor before making your enrolment decision.