Live Online classes with Certificate & 5 projects
Environmental setup
Guesstimate question
Analytical thinking
Data Science overview
Excel features
Excel formulas
Analytics within Excel
Visualization in Excel
DATA MINING FROM SQL
DATABASES AND MONGODB 3
Data mining
Mining from Sqlite3
Mining from MongoDB
Loading data from CSV
Interacting with Cloud data
Analytics Quiz
Working with Excel data ribbon
Setting up a cloud database
PYTHON FUNDAMENTALS
NUMPY ARRAY
LEARNING CHECKPOINT 2

The CRISP-DM Framework
Revisiting important concepts
String formatting
List and tuples
Dictionary and sets
Comprehensions
map, filter and lambda
n-dimension arrays
Array properties
Array functions
Radom number arrays
Python Quiz
Numpy array functions test
Pandas DataFrame manipulation
7 PANDAS
Reading CSV data
DataFrame properties
DataFrame slicing and sorting
Data aggregations and joining
DATA VISUALISATION WITH
MATPLOTLIB AND SEABORN
EXPLORATORY DATA
ANALYSIS (EDA)
LEARNING CHECKPOINT 3
Graph forms and markers
Line plot
Scatter plot
Bar graph and histogram
Pie chart
Cohort analysis with seaborn
Data investigation & pattern discovery
Anomaly detection
Model selection
Statistics Quiz
Subplots and HeatMap
EDA assigment
11 STATISTICS (PART-1)
Statistical significance
Basics statistical measurements
Probability distributions
Hypothesis testing
STATISTICS (PART-2)

Probability Distributions
Discrete Distribution
Binomial Distribution
Probability Density Functions
Continuous Distribution
Normal Distribution
Continuous Distribution
Standard Normal Distribution
Central Limit Theorem
Setting Up a Hypothesis test
One tailed and two-Tailed test
Type I and Type II error
Significance of P value
T Distribution
Two Sample Mean Test
A/B testing
14 MACHINE LEARNING
Simple Linear Regression
Multiple Linear Regression
Logistic Regression
Support Vector Machines
Naive Bayes
Decision Tree
K-nearest neighbours
K means/ K median
Principle Component Analysis
Apriori Algorithm
Supervised Learning
[ Regression ]
[ classification ]
Unsupervised Learning
[ Clustering ]

COURSE HIGHLIGHTS

Duration: 2 months
Course Cycle: Mon, Wed, Thr, Sat
Class timing: 8:00 PM - 10:00 PM (IST)
Lab setup: Python3, MSExcel, Sqlite3,
Pymongo, Numpy, Pandas, Matplotlib,
Seaborn, Statsmodels, Scikit-learn, Git

CAPSTONE PROJECT
Industry project with real-world
data sets

ADD-ON SERVICES
Course completion certificate
Placement preparation kit
Backup classes
Discussion forum
Community access
Comprehensive Notes
Practice Datasets
Live mentoring