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Machine Learning Specialization

Machine Learning algorithms are the backbone of Predictive Modelling. This is where the Crux of Data Science lies. The end objective of solving a data science problem is finding the patterns in the data and represent that in the form of a Data model. The algorithms taught in our course cover almost all of the problems data scientists solve on a regular basis.

LEARN

  • The Machine Learning Landscape
  • Linear & Logistic Regression
  • Regularization
  • Training Models
  • Support Vector Machines
  • Decision Trees
  • Ensemble Learning and Random Forests
  • Dimensionality Reduction
  • Unsupervised Learning Techniques
  • End-to-End Machine Learning Project

FEATURES

  • Instructor led online LIVE session for entire course duration
  • Small batch size– Personalized attention
  • Highly Interactive sessions (Two way participation – Chat and Speech)
  • Highly experience and Qualified Trainers [Analytics experts, 10+ years industry experience (IITians)
  • In-depth case study discussion – Domain Specific Projects
  • Lifetime Access to Session Recordings & Case studies through Learning Manangement Portal
  • Career guidance and Placement Assistance
  • Course Completion Certification
  • Highly approachable faculty – 24*7 support available
  • Reattend LIVE sessions -If you miss a Lecture due to some reason

LEARNING OUTCOMES

  • Understand the fundamentals of machine learning, Superevised and Unsupervised Algorithms and Mathematics behind it.
  • Ability to design, choose and implement different Machine Learning algorithms to solve real world problems.
  • Ability to optimize the Data model using various techniques like tuning hyperparameters, curve fitting etc.

DEMO VIDEOS

COURSE DURATION

60 hours

SESSION TIMINGS

Weekends – 6 hours
9.30 PM IST to 12.00 PM IST

CURRICULUM

Machine Learning [LIVE 55 hours]

Python is a critical tool for Data Science. In this module participants learn Python programming from basic to advanced level using  Jupyter notebooks. Here, participants create, subset and manipulate various data structures. Specific libraries like  NumPy, Pandas and  Matplotlib that are popular for Data Analysis are covered in depth. 

  • Introduction to Supervised and Unsupervised Learning
  • Linear Regression with Multiple Variables
  • Logistic Regression
  • Decision Trees [CART]
  • k-Fold Cross Validation
  • Bagging and Bootstrapping
  • Random Forest
  • Gradient Boosting (XGBoost)
  • Principal component Analysis
  • K-means clustering
  • Hierarchical Clustering
  • Market Basket Analysis
  • KNN
  • Support Vector Machine
  • Naive Bayes
  • Time Series Analysis

Machine Learning [ RECORDED ]

By this time the Machine Learning fundamentals are known and participants understand how to decipher data science problem, find patterns in the data and represent that in the form of a Data model. The focus shifts to learning few more algorithms and providing you more tools to take on the Data Science problems.

  • REGULARIZATION
  • SUPPORT VECTOR MACHINES
  • NAÏVE BAYES
  • TEXT ANALYSIS
  • TIME SERIES ANALYSIS

CASE STUDIES

  • Predicting wine quality
  • Healthcare Budget estimation for an Insurance company
  • Predicting the quality of healthcare
  • Predicting hotel demand
  • Creating a recommendation system for movies
  • Sentiment Analysis on Tweets from Apple to gauge customer perception
  • Predicting the quality of healthcare using Analytics
  • Predicting the demand in hote

TEACHING METHODOLOGY

  • Personalized attention
  • LIVE instructor-led training throughout the training duration
  • Entirely Hands-On – Case Study based
  • Practical Inputs from real-time scenarios
  • Lifetime Access to Session Recordings

INSTRUCTOR PROFILE

Himanshu Arora

Himanshu Arora

(IIT, Bombay – 10+ years experience in Data Science) A machine-learning practitioner, fascinated by the numerous application of Artificial Intelligence in the day to day life.

I enjoy applying my quantitative skills to new large-scale, data-intensive problems.I am an avid learner keen to be the frontrunner in the field of AI. I enjoy learning new technologies at work and strive hard to acquire finesse in skills that I have honed over my career.

Trained 5000+ participants in R, Machine Learning, Tableau and Python, Big Data Analytics and Deep Learning at Dimensionless

Conducted workshops and training on Data Analytics for Corporate and Colleges

He possesses knowledge of a wide variety of machine learning and deep learning algorithms.

Read More

Pranali

Pranali

Pranali is a professional Data Science Trainer with more than 15 years of experience in the teaching various training programs on Databases, Programing and Machine Learning.
Her core competency include Databases, Data Science and Big Data. She holds a Masters degree in Computer Engineering from University of Pune.

FAQS

Why Should I Learn Machine Learning from Dimensionless?

  • Dimensionless Tech provides best online data science training that provides in-depth course coverage, case study based learning, entirely Hands-on driven sessions with Personalised attention to every participant. We guarantee Learning.

What Are The Various Modes Of Training That you Offer?

  • We provide only instructor-led LIVE online training sessions. We do not provide classroom trainings.

How is your online training better than classroom training?

  • In physical classrooms, students generally feel hesitant to ask questions. Unlike other online courses,  we allow you to speak in the session and ask your doubts. The interactivity level is similar to classroom training and you get it at the comfort of your home. If you miss any class or didn’t understand some concepts, you can’t go through the class again. However, in online courses, it’s possible to do that. We share the recordings of all our classes after each class with the student. Also, there’s no hassle of long-distance commuting and disrupting your schedule.

Can I ask my doubts during the session?

  • All participants are encouraged to speak up and ask their doubts. We answer all the doubts with same sincerity.

Is there a hardware requirement for this course?

  • Any laptop with 2GB RAM and Windows 7 and above is perfectly fine for this course. For large data, the access will be given on the online lab.

What if I miss a session, due to some unavoidable situation?

  • We understand that while balancing your personal and professional commitments you might miss a session. Hence, all our sessions are recorded and the recordings are shared with you through our Learning Management Portal.

How long will I have access to the Learning Management Portal?

  • You will have lifetime access to the portal and you can view the Videos, Notes, Books, Assignments as many time

What Kind Of Projects Will I Be Working On As Part Of The Training?

  • During the training you will be solving multiple case studies from different domains. Once the LIVE training is done, you will start implementing your learnings on Real Time Datasets.  You can work on data from various domains like Retail, Manufacturing, Supply Chain, Operations, Telecom, Oil and Gas and many more. You would be working on multiple projects so that you can gain enough content and confidence to enter into the field of Data Science.

Do You Provide Placement Assistance?

  • Yes, we provide you with real-time industry requirements on a daily basis through our connect in the industry. These requirements generally come through referral channels, hence the probability to get through increases manifold. The HR from the team, helps you with Resume Building and Interview Preparation as well.

Do I get a Course Completion Certificate?

  • Yes, we will be issuing a course completion certification to all individuals who successfully complete the training.

CAPSTONE PROJECTS

Sentiment analysis measures the attitude and belief of the customer towards the service or product.


Your task is to make a sentiment analysis model that takes the review of a customer and returns whether the review is positive or negative.

Accurate forecasting of increasing coronavirus is important. It will help the medical institutions and government to plan their strategies accordingly.

Your task is to forecast the cumulative number of confirmed COVID-19 cases across the world.

The task here is to incorporate all the various components of football players and display them in a single environment using clustering, so that users can select their players of interest by one click instead of selecting the features manually.

Airline companies use techniques to systematically allocate airfare prices. The task given here is to accurately predict the price.

This will help the passengers to decide a specific airline as per their budget and save their time and money.

When we order food, questions such as ‘Where is my food?’ or ‘When will my food arrive?’ often emerges in our minds.

In this project, you will be given data of thousands of restaurants in India and your task is to predict the food delivery time.

Food quality needs to be assessed from time to time. Your task is to make a ML model that predicts whether a specific facility will pass or fail the food quality assessment, by using the dataset which was collected by the food inspection department.

Recommendation system broadly recommends products to customers best suited to their tastes and traits.

Your task in the project is to predict and recommend a few hotels to a user that he/she is more likely to book out of thousands of hotels available.

Sales Forecasting tells the future sales based on the current and past sales data.

You are given historical sales data of 45 Walmart stores located in different regions and your task is to predict the weekly sales for each department of every store.

COURSE PROJECTS

California Housing Price

Aim of the project is to predict the housing prices for a district from the 1990 California Census dataset.

Health Care Quality Assessment

Dataset consists of the claims data for the insured patients to predict the quality of healthcare received.

Baseball Players

The task is to predict the salary of baseball players playing in major leagues from the StatLib Dataset.

Heart Disease

The aim is to identify trends in heart data to predict cardiovascular events that can lead to heart disease.

Movies Recommendation

The aim is to build a movie recommendation system based on genres. The data used is gathered from MovieLens.

Automobile Sales classification

The project is to predicts monthly sales of the Hyundai Elantra in the United States from the given dataset.

Framingham Heart Study

The data of Framingham Heart Study is a cardiovascular cohort study used to predict and prevent heart disease.

Mall Customer Segmentation

The Mall Customers data set have information of customer that can be used to carry out customer segmentation.

Credit Risk Modelling

The task is to identify if a person will be able to pay/default the loan amount from the loan dataset.

HAPPY EMPLOYERS

POPULAR COURSES

Deep Learning

Duration: 60 hours

Testimonials

Farheen Siddiqui

Business Analyst, Chennai Branch, Fortune India 500 Company

I joined this training curriculum to have a transition in my career. What they say is exactly what they do. Highly knowledgeable and supporting faculties. The HR support informs us about the job openings from time to time. Apart from teaching they conduct webinars from experienced data scientists.

Avinash Vasista

Senior Consultant, Hirepro Consulting Pvt. Ltd.

Dimensionless – Knowledge Encyclopedia

Dimensionless has helped me to lay a strong and deep pillar for my Data Science Career, their teaching methodology on their online platform is very effective, interactive & flexible. It is a privilege to learn the concepts from industry experts. Kudos to all teaching and non-teaching staff for the great ongoing learning experience across Python, ML, R & Tableau.

Eshan Kaul

Associate VP, Corporate & Investment Banking, JP Morgan Chase

It’s an almost impossible task to take everyone along when the class mix is so diverse. But the trainers would spend the first 5-10 minutes of each session on clearing ANY doubts or any questions, anyone would have. The trainers were also judicious to push some questions towards the end of the session when more time would be needed to address a certain query.

Ruchika Patro

Sr. Software Engineer, United Health Group

I joined a data science course in October ’18. Here the instructors teach so patiently and start all topics from the basics. The topics covered are purely fit for the industry. I got a good understanding of all topics after going through this course and I am now well fit for attending any interviews.

Thanks, Dimensionless for this course with this price.