Data Science

Days

Course Detail

Day 1

Introduction Data Science

Benefits and uses – facets of data – Data Science Process: Overview – Defining research goals – Retrieving data – Data preparation – Data Mining – Data Warehousing – Basic Statistical descriptions of Data

Day 2

DESCRIBING DATA

Types of Data – Types of Variables -Describing Data with Tables and Graphs

Day 3

Data Preprocessing

Collecting, Cleaning, and Validating Data with examples

Day 4

Basics of Python

input and ouput function in python, Variables, expression, condition and function, data types, basic opearators

Day 5

Python Libraries for Data Processing

Basics of Pandas, NumPy , SciPy, Scikit-learn,TensorFlow,Keras

Day 6

Python Libraries for Data Visualization

Importing Matplotlib – Line plots, Box Plot,Heatmap, Scatter plots,Seaborn, Plotly

Day 7

Exploratory Data Analysis using Python

"Reading dataset
Analyzing the data
Checking for the duplicates
Missing Values Calculation"

Day 8

Exploratory Data Analysis using Python

"Univariate Analysis
Bivariate Analysis
Multivariate Analysis"

Day 9

Machine learning

Supervised, Unsupervised, reinforcement learning , Application of Machine learning in various sectors

Day 10

Application, Ethics and Security in Data science

Applications of Data Science, Data Science and Ethical Issues- Discussions on privacy, security, ethics- A lookback at Data Science- Next-generation data scientists