Why Machine Learning?

Every organization is betting big on machine learning to fuel their growth and the demand for data scientists has skyrocketed. Machine Learning is not only the most lucrative career option today (average salary for Data Science roles in India is 10LPA+ as per Glassdoor) but will soon become an essential skill for everyone. Hence investing time and effort to learn Machine Learning will give every student a competitive advantage when they step out in the job market tomorrow.

What will I learn?

Introduction to Machine Learning
modules icon 12 Modules
  1. 1. Introduction to Machine Learning
  2. 2. Python for Machine Learning
  3. 3. Machine Learning Life Cycle
  4. 4. Data Exploration and Manipulation
  5. 5. Data Manipulation and Visualization
  6. 6. Build Your First Model
  7. 7. Evaluation Metrics
  8. 8. k-NN
  9. 9. Selecting the Right Model
  10. 10. Linear Models
  11. 11. Decision Trees
  12. 12. Feature Engineering
Advanced Machine Learning
modules icon 11 Modules
  1. 1. Welcome to the Applied Machine Learning Course
  2. 2. Basic Ensemble Model and Advance Ensemble Techniques
  3. 3. Hyperparameter Tuning
  4. 4. Dimensionality Reduction (Part I)
  5. 5. Working with Text Data
  6. 6. Naïve Bayes
  7. 7. Support Vector Machine
  8. 8. Working with Image Data
  9. 9. Advance Dimensionality Reduction
  10. 10. Unsupervised Machine Learning Methods
  11. 11. Automated Machine Learning
Structured Query Language (SQL) for Data Science
modules icon 11 Modules
  1. 1. Introduction to Databases
  2. 2. Installing MySQL/ MariaDB
  3. 3. Getting started
  4. 4. Modifying Databases structures
  5. 5. Importing and Exporting Data
  6. 6. Data Analysis
  7. 7. Real-Life Project - Descriptive Analytics of FIFA 19 Players
  8. 8. Getting Data from Multiple Tables
  9. 9. Introduction to Indexing
  10. 10. MySQL built-in functions
  11. 11. Manipulate MySQL from Python
Ace Data Science Interviews
modules icon 9 Modules
  1. 1. Overview - Ace Data Science Interviews
  2. 2. Overview - The 7 step Data Science Interviews process
  3. 3. Step 1 - Understanding roles, skills, Interviews Framework
  4. 4. Step 2 - Building Your Digital Presence
  5. 5. Step 3 - Building Resume and Applying for Jobs
  6. 6. Step 4 - Telephonic Interviews
  7. 7. Step 5 - Assignments
  8. 8. Step 6 - In-Person Interview(s)
  9. 9. Step 7 - Post Interview Follow-ups
Detailed Table of Content

Who will be my teachers?

Kunal Jain

Kunal Jain

Founder, Analytics Vidhya

IIT Bombay (2006), 12+ years of experience in reputed companies like Capital One, Aviva Life Insurance etc.

Sunil Ray

Sunil Ray

Chief Content Officer, Analytics Vidhya

6+ years of experience in using data to solve business problems for several Insurance companies.

Anand Mishra

Anand Mishra

Head of Engineering, Analytics Vidhya

IIT Kanpur (2011), experience in brands like MudraCircle (Founder), HTMedia, Tickled Media, etc.

Pranav Dar

Pranav Dar

Senior Editor, Analytics Vidhya

Experienced professional in data visualization and data science having penned 200+ articles.

Aishwarya Singh

Aishwarya Singh

Data Scientist, Analytics Vidhya

Data science enthusiast having penned 70+ articles in applications of machine learning.

How will I learn?

Video Tutorials
Quizzes
Assessment Tests
Practice Exercises

What projects will I build?

1. Real-Life Project - Descriptive Analytics of FIFA 19 Players

In this project, we will take a real-life dataset of FIFA19 players and do descriptive analytics on it. We will go through the process of how data is understood, transformed, and how we get answers and insights from our data.

2. Food Demand Forecasting

A meal delivery company has a number of dispatch centers in multiple cities. You have to help these centers with demand forecasting for upcoming weeks so that these centers can plan the stock of raw materials accordingly.

3. Malaria Detection

Automatic detection of Malaria from blood smear images can go a long way in our battle against this deadly disease. In this project, using deep learning, we will try to predict whether the sample is from an infected person.

4. Web Page Classification

Classification of a Web page content is important for search engines to identify web pages that are relevant to a particular topic. In this project, you will build a web page classifier that achieves just that.

5. NYC Taxi Trip Duration Prediction

Predicting trip duration is important for many online cab services such as Uber & Ola. This project will cover techniques to accurately predict trip duration for taxi trips in New York using data from TLC commission New York.

6. Customer Churn Prediction

A bank wants to retain its customers and you have the customers’ demographics such as age, gender & their transaction history. Your task as a data scientist would be to predict which customers will leave the bank.

7. Predict survivors from the Titanic tragedy

We are provided with information about people on the Titanic. Based on the given data, we will apply machine learning algorithms to predict which passengers survived the tragedy.

8. Sales Prediction for a large Supermarket

The data scientists at BigMart have collected sales data for 1559 products across 10 stores in different cities for an entire year. You will build a predictive model to forecast the sales of each product at a particular store.

How will my doubt get solved?

Forum

What certificate will I get?

At the end of your specialization, you will be awarded a joint certificate of completion from Internshala and Analytics Vidhya.

Certificate

What placement assistance will I receive?

30 minutes call with practicing Data Scientist
Get access to curated Data Science internships and jobs
Get life long mentorship from an experienced Data Scientist

Enrollment Form

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