Course Detail

Machine Learning Course

Machine Learning Course - DIGITAL VIDYA

: 1000 INR - 5000 INR

Course Detail

Course Description

Landscape of Machine Learning

  • 2.3 Million Machine Learning Jobs will be created by 2020
  • Average Salary Base for Machine Learning Jobs is $146,085
  • 10,000+ Monthly Machine Learning Job Openings
  • Initial Salary 5,00,000 – 12,00,000 INR Per Annum
  • Machine Learning Engineers Rule The Top 10 AI Jobs List


In-Depth Advanced Modules 


Hands-on Projects


Career Mentoring 


Hours of Live Classes


Placement Partners




Exclusive Offers!


Certification Validity 


Job Assistance

Know more about our Machine Learning Course

Why Should You Take this Machine Learning Course?

Machine Learning is one of the hottest career choices today. It is one of the fastest-growing tech employment areas with jobs created far outnumbering the talent pool available.

According to Gartner, 2.3 million Machine Learning Jobs will be generated by 2020. Indeed job trends report also reveals that in terms of most in-demand, AI jobs, Machine Learning Engineer tops the chart with 29.10% increase in job postings.

Today, every industry is going gaga after Artificial Intelligence. This makes it ideal to take up a Machine Learning Course.

By bringing better career opportunities, Online Machine Learning Courses have become the shining star of the moment. 

Who is this Course For?

– People with knowledge of Python Programming
– Candidates with an understanding of Statistics, Algebra & Calculus

Our Machine Learning Online Course Enrollments Map

  • Students40%40%
  • IT Professionals60%60%

13 Modules

Machine Learning Online Course Curriculum Details

  • Graphically Displaying Single Variable
  • Measures of Location
  • Measures of Spread
  • Displaying relationship – Bivariate Data
  • Scatterplot
  • Measures of association of two or more variables
  • Covariance and Correlation
  • Probability
  • Joint Probability and independent events
  • Conditional probability
  • Bayes’ Theorem
  • Prior, Likelihood and Posterior
  • Discrete Random Variable
  • Probability Distribution of Discrete Random Variable
  • Binomial Distribution
  • Continuous Random Variables
  • Probability Distribution Function
  • Uniform Distribution
  • Normal Distribution
  • Point Estimation
  • Interval Estimation
  • Hypothesis Testing
  • Testing a one-sided Hypothesis
  • Testing a two-sided Hypothesis
Learn more about our Machine Learning Course Curriculum


15+ Hrs of Hands-on Assignments


Hands-on Machine Learning Course Assignments 

Well researched assignments have the potential to take the participants on an exciting journey to execute their learnings. That’s our mantra at Digital Vidya.

Each assignment of Digital Vidya’s Machine Learning Course is designed with a focus to provide the best practical experience. Our module assignments to learn Machine Learning focus on enhancing the confidence of our participants.

Our Assignments are close to the actual occurrences in the industry out there. These assignments will be a propeller to helping you learn Machine Learning practically. 


Statistics: Probability, Hypothesis Testing
Multiple Linear Regression & Quadratic Regression Analysis
Introduction to Trees, Decision Trees, Ensemble Learning (Random Forest)
Classification Introduction, Logistics Regression & Text Analysis Using Classification Algorithms
Unsupervised Learning, Unsupervised Learning Techniques-K Means Clustering, Hierarchical Clustering
Bias-Variance Trade-off, Model Evaluation Techniques
Logistic Regression Model Tuning
Know the complete offering of our Machine Learning Course

Capstone Projects on Offer

Best in Class Capstone Projects to Learn Machine Learning

To learn Machine learning in the best possible and hands-on method, Digital Vidya’s Machine Learning Course comes with best in class capstone Projects. At the end of each batch, we hold a Capstone Project competition that is open for our students. Successful participants win prizes and recommendations from their lead trainers.

Natural Language Processing

Duration: 3 Weeks

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Project Description:

This is one of the most applied areas for AI, Data Science, and Machine Learning across domains and industries. The real world is filled with mostly messy text data, and handling text is an important step towards making smarter algorithms. Using IMDB dataset from the movie domain, the learner will apply the most common concepts of NLP.

Key Takeaway:

This project will empower the learners to build intermediate skills in the natural language processing domain. A few of the fundamentals of working with textual data covered in this project are:

  1. Remove stop words
  2. Apply Stemming and Lemmatization
  3. Create a cluster of words
  4. Build a sentiment analysis model and a clustering model

Healthcare Analysis

Duration: 3 Weeks

Healthcare Analysis 2

Project Description:

Electroencephalography (EEG) is an electrophysiological monitoring method to record the electrical activity of the brain. For this project, we will use the large EEG database at UCI Machine learning repository. This data arises from a large study to examine EEG correlates of genetic predisposition to alcoholism. One fascinating question is whether the patterns are different for an alcoholic and regular subject?

Key Takeaway:

This capstone project focuses on EEG data analysis, giving an opportunity for students to learn through complexities in dealing with such complex real-world data. The project contains the following exercises:

  1. Parse and store in an easily understandable and readable form
  2. Exploratory data analysis to better understand the data
  3. Using Statistical concepts like Hypothetical testing
  4. Identify features to predict whether a subject is alcoholic or not
  5. Use machine learning algorithms to develop a suitable classifier

Bank Marketing

Duration: 3 Weeks

bankmarketing 3

Project Description:

The banking industry is working in a very competitive environment and needs to strategize to grow its business.  This project is related to the marketing campaigns related to term deposits, making an interesting multi-disciplinary work that mixes both the finance and the marketing domain.

Key Takeaway:

The approach to this project is to think, define, design, code, test and tune your solution, in such a way that you apply all aspects of the data science process. The data is a real-world data with unclean and null values.

The objective is to:

  1. Build the model to predict if a customer will subscribe
  2. Identify influential factors to form marketing strategies
  3. Improve long-term relationship with the clients

Deep Learning Based Project

Duration: 3 Weeks | Price: ₹5000 (Including Tax)

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Project Description:

E-Commerce has experienced considerable growth since the dawn of the internet as a commercial enterprise. Deep Learning excels at identifying patterns in unstructured data and can predict the class of an uploaded image applied on eCommerce context. This project is an attempt to replicate virtual store assistance through image recognition over an eCommerce Fashion MNIST dataset.

Key Takeaway:

This project focuses on the implementation of Neural Networks to solve complex unstructured data problems. The objective is to:

  1. Build the model to classify the various categories (analytic vertical) of clothing/fashion related images.
  2. Understanding the implementation of deep learning concepts through Tensorflow and Keras.
  3. Model optimization by tuning hyper-parameters and implementing dropout layers.

Institute Overview

Patna, Bihar, India

About Digital Vidya   Digital Vidya is Asia’s leading professional training company focusing on imparting new-age skills to individuals & organizations. Since 2009, over 61,000+ professionals (including CXOs) from 16,... Read More

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