Why Choose Tech Mahindra Certification Program in Data Science?
Real world datasets from companies like Nike, Yelp, Amazon, Netflix etc. are provided to our students
Recommender systems for Groceries
This data contains 10 variables and over 1000 observations on online grocery purchases
"Iowa City - Housing data pricing analysis "
The dataset contains 80 variables & over 1000 observations on Iowa city real estate
Build Chatbot using slack Class
In this project chatbot allows us translate user submitted conversations from English to Hindi
Analysis of Gun Violence in USA
"The dataset contains 6 attributes with 501 instances of Children killed & injured across all the states of the USA."
Adult Income Dataset
The dataset has 15 attributes & 32562 instances about adult income and some data of other parameters
Supermarket Purchase Analysis
The dataset contains 6 variables & 702 observations identifying shopping behaviour of a segment of customers.
Exclusive Interview preparation guides, Career Support, Placement Opportunity and many more..!
Our world-class faculty are experienced working professionals working in senior positions of top-tier companies
What are you going to learn ?
Module 1: Data Science Introduction & Use Cases
Module 2: Python Basics: Basic Syntax, Data Structures
Module 3: Python Basics: Loops, If-elif statements, Functions, Exception Handling
Module 4: Statistics 1: Measures of central tendency, Population, Sample, Probability Distribution
Module 5: Statistics 1: Normal and Binomial Distribution, Random Variable, Pictorial Representations
Module 6: Python Advanced: Numpy, Pandas
Module 7: Python Advanced: Data Manipulation, Matplotlib
Module 8: Exploratory Data Analysis: Data Cleaning, Data Wrangling
Module 9: Exploratory Data Analysis: Data Visualisation
Module 10: Exploratory Data Analysis: Case Study
Module 1: Introduction to Tableau
Module 2: Data visualisation
Module 3: Analytics concepts with Statistics - I
Module 4: Analytics concepts with Statistics - II
Module 7:Analytics Concepts using caluclated feilds
Module 6: Analytics concepts for integrating dashboards
Module 7: Mini project workshop - Visual Analytics
Module 8: Integration of Tableau with Python
Module 1: ML Introduction & Use Cases
Module 2: Statistics 2 - Inferential Statistics
Module 3: Linear Regression
Module 4: Logistic Regression
Module 5: Decision Trees, Random Forest
Module 6: Modelling Techniques (PCA, Feature Engineering)
Module 7: KNN, Naive Bayes
Module 8: Support Vector Machines(SVM)
Module 9: Clustering, K-means
Module 10: Time Series Modelling
Module 1: Market Basket Analysis & Apriori Algorithm
Module 2: Recommendation System
Module 3: Recommendation System - Mini Project
Module 4: Dimensionality Reduction (LDA, SVD)
Module 5: Dimensionality Reduction (Matrix optimisation)
Module 6: Anomaly Detection
Module 7: XG Boost
Module 8: Gradient Boosting Machine(GBM)
Module 9: Stochastic Gradient Descent(SGD)
Module 10: Ensemble Learning - I
Module 11: Ensemble Learning - II
Module 12: Introduction to Neural Networks
Module 1: Introduction to NLP & Deep Learning
Module 2: Word Embeddings
Module 3:Word Window classification
Module 4:Intro to AI Networks
Module 5: Recurrent Neural Networks for Language modelling
Module 6: Intro to tensorflow
Module 7: Gated Recurrent Units(GRUs), LSTMs
Module 8: Recursive Neural network
Module 9: Convolutional Neural Networks for classification
Module 10: Dynamic Memory Networks
All the courses are instructor-led and take place online. The online interface lets you and the faculty have a two-way interaction. It’s as good as sitting in a physical classroom.
All classes take place over the weekends in the mornings. There’ll be one class of 2 to 2.5 hours on Saturdays and Sundays each. This means that you can now acquire in-demand skills without compromising on your schedule.
Yes, the recordings of the trial classes are uploaded.
In physical classrooms, students generally feel hesitant to ask questions. 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.
We believe that unless you implement the concepts studied in the classes, you are unable to join the dots and hence can’t see the entire picture. Our capstone projects let you apply the learned concepts to real-world data sets. You’ll be working on real-time data-sets (which can run in 100s of MBs or possibly in GBs!) which you get to choose from a variety of domains such as retail, finance, social media, healthcare, etc. These datasets have been curated from top sources such as World Bank, US Health Department, Carnegie Mellon, Stanford and many more.
You’ll get access to our virtual computing lab through the login credentials provided to you. The virtual machines will enable you to work on “Big Data” sets for your projects and practice hands-on too.
We provide certification of completion to students who attend at least 70% of the classes. After the course ends, we conduct a certification exam that evaluates them on the skills they have learnt. Certification from Tech Mahindra is provided to only those who clear the exam. The exam is purely case-based and not even a single theory question is asked.
We provide career workshops and industry immersion sessions to help you become ready for roles you are aspiring for. We also help you in resume review and interview preparation. If you diligently follow our advice, you should start getting interview calls as soon as you finish the course.