Title : DATA SCIENCE - Professional Course
Hours : 60 Hrs
Batches : Weekday ( Mon - Fri )|Weekend ( Sat & Sun )
60 Hours of
Class Room Training
30 Sessions of
Class Room Training
90 Hours of
50 Coding Tasks
For Interview Purpose
We provide a Professional level Data Science Course that will establish your mastery of data science and analytics techniques using Python Libs, you’ll learn the essential concepts and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing.
You should be able to
- Understand data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing.
- Understand the basics of Statistics & essential concepts of Python programming for Data Science.
- Perform high-level mathematical computing using the NumPy package and tools provided in the Pandas package.
- Gain expertise in machine learning.
- Anyone aspiring to learn new technology and pursue their career in Data Analytics can take this course.
- Python Programming knowledge is desirable, but not mandatory.
4:30 PM to 6:30 PM | Monday to Friday | 5 Days/Week | 6 Weeks Course
4:30 PM to 6:30 PM | Saturday & Sunday | 2 Days/Week | 15 Weeks Course
- Class-1 : Overview of Analytics
- Class-2 : Basics of Statistics
- Class-3 : Probability
- Class-4 : Statistical Measures
- Class-5 : Hypothesis, Parametric & Non-Parametric Tests
- Class-6 : Introduction to Data Management
- Class-7 : Statistics and EDA
- Class-8 : Data Visualization
- Class-9 : Linear Regression
- Class-10 : Logistic Regression
- Class-11 : Time Series
- Class-12 : Machine Learning
- Class-13 : Decision Trees and Random Forests
- Class-14 : K-Means Clustering
- Class-15 : Principal Component Analysis & Cross Validation
- Class-16 : Naive Bayes
- Class-17 : Neural Network Basics
- Class-18 : Installation and Python Basics
- Class-19 : Python Basics and String Manipulation
- Class-20 : Data Structures in Python
- Class-21 : Data Frame Manipulation
- Class-22 : Libraries like Numpy,Pandas
- Class-23 : Simple Regression Analysis using Python
- Class-24 : Multiple Regression using Python
- Class-25 : Decision Trees using Python
- Class-26 : Time Series using Python
- Class-27 : Data Visualization using Matplotlib
- Class-28 : Introduction to Tabulae
- Class-29 : Real World Case study -1
- Class-30 : Real World Case study -2