Features
- Lectures - 14
- Duration - 8 Weeks
- Case Studies and Assessment - 5+
- Delivery Mode - Online/Offline
- Batches - Weekdays/Weekend
- Capstone Projects - 15 projects( Choose anyone)
Is learning Data Science worth or not? Are you prepared to learn Data Science or not? What are the steps to move ahead to learn Data Science? If you have all these questions in your mind then this program is for you.
Program Overview
- This program is specially designed to give a strong foundation to become a Data Scientist. You will get a brief knowledge on Statistical Analysis, Data Preparation and Machine Learning. After completing this course, you will be able to solve business problems using Data Analytics.
Program Structure
- Pre-Learning: Before you come in, get ready for the program. You will get a series of online recorded tutorials on Basic Statistics, Excel and Introduction to Data Science.
- 40 Hours Program: Here, you will get experience in Python Programming, Statistics and hands-on experience on Machine Learning & Deep Learning Techniques.
- Post Program: Learning does not stop here. After completing the program, you will work on capstone project, case studies. Doubt clearing session is provided post program. You will be working on any 1 capstone project from the list of few projects on your choice.
Eligibility:
- Education – Graduate in Math, Science, Commerce, Statistics, Economics or Management.
- Work Exp – Fresher or Experienced in any disciplinary field.
Sample Certificate
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Introduction to Advanced Statistics
Introduction to Statistics, Descriptive Statis, Population and Sample, Types of Data, Percentile, Quartile, IQR, Corelation and Covariance, Measure of Central Tendency, asymmetry and variability , Skewness, Kurtosis, Central Limit Theorem, Confidence Interval, Hypothesis Testing, p-value, T-test, Z-test, F-test
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Python Programming
Introduction to python, Variables, Operators, Datatypes and its operations, Data structures and its operations, Functions, **kwargs, *args, Module, Class, Numpy, Pandas, Matplotlib, Seaborn
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Data Warehousing
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Machine Learning ,Supervised Learning , Unsupervised Learning
Introduction to Machine Learning, Types of Machine Learning, Linear regression, Logistics Regression, Support Vector Machine, K Nearest Neighbour, Naïve Bayes, Decision Tree, Random Forest, PCA, Clustering
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Introduction to Deep Learning
Introduction to Deep Learning, Feed Forward Network, Fully Connected Network Activation Functions, Optimizers
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Hands-on Session on Live Project
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Program Benefits
- ✔️ Cutting Edge Curriculum: Hand crafted Course content made by Experts from various Industries. Learn through Practical case studies and multiple projects.
- ✔️ Build Solid Foundation: 40 hours focused course on Statistics and Machine Learning.
- ✔️ On the Go Learning: Online accessible E-learning Material, recorded lectures, case studies and Research Paper through our system.
- ✔️ Industry Mentorship: Get 1 to 1 guidance from Industry experts and start your career in Data Science.
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Skill you will possess post program
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Capstone Projects
- ✔️ Credit card Risk Analytics
- The most effective way to learn Data Science is to learn practically. Once the program gets finished candidates will be provided with a few Projects based on Machine Learning. You are advised to choose any 1 project according to your domain and your interest. Some examples of capstone project:
- ✔️ Prediction of Future security prices
- ✔️ Sales Prediction for Big Mart
- ✔️ Food Demand Forecasting
- ✔️ Project for a real estate company that wants to Predict the prices of houses based on different parameters.
- ✔️ Black Friday Sales Prediction