3 Days Live Training on Data Analysis using Python

About the Course

PART 1: Introduction, Applications and Frameworks, Get Started with programming, Variables and DataTypes, Operators and Expressions , Control Structure, Sequence Types, Dictionaries and Sets ,List Comprehensions, Functions, Local, Non Local & Global Variables, Anonymous and LambdaFunctions

PART 2: Environment Set Up , Anaconda, IPython Shell, IPython Notebooks, Pycharm, Spyder IDE, RunPython scripts, Loading packages, namespaces

PART 3: Numerical Analysis using NumPy, Introduction to NumPy, NumPy overview , Creating NumPyarrays , Doing math with arrays , Indexing and slicing , Records and dates , Downloading andparsing data files , Using Scipy

PART 4: Accessing and Preparing Data, Acquiring Data with Python, Loading from CSV files, AccessingSQL databases, Cleansing Data with Python, Stripping out extraneous information, Normalizing data, Formatting data, Debugging, Code profiling

PART 5: Data manipulation with Pandas, Pandas overview , DataFrames in pandas , Using multilevelindices, Series in pandas , Statistical analysis , Grouping, aggregating and applying, scipy.stats ,Tabular Data Analysis with Pandas , Data Munging in Python using Pandas

PART 6: Visualization Tools , Overview , Mathplotlib , Numpy , Seaborn , Input: 2D, samples, and features, statistical graphics , Data Reporting , Extract datasets for specific reports (routine and adhoc) ,Prepare reports on observed trends and patterns( Daily/weekly/monthly & quarterly , Developgraphs, reports, and presentations based on observation., Create management dashboards based on derived data collections.

PART 7: Web Scrapping & NLK , NLK, Scrapy.py, urllib , Pylib , Beautiful soup

Course Objective

Learn basics of python programming

Environment Set Up and Using Various IDE

Working on Numerical analysis and Data Manipulation Techniques

Using and Applying Data Visualization and Web Scraping API’s

Generate simple reports and dashboards

Who is the Target Audience?

Fresh graduates who completed academic studies recently and get Hands on Programming.

Those who want to stay ahead in Data Analytics, Data science and frameworks

Candidates desirous of working in IT Software and Support career.

Managers and leads to manage Python and data science projects .

For those willing to switch from legacy coding to new generation Programming

Those who are willing to migrate from Non IT to IT Jobs.

For those who are looking for career breakthrough in software Development.

Basic Knowledge:

Student can start as a fresher to Learn Python.

Basic knowledge of using computer, tools and utilities

Simple analytical and logical Thinking

Interest in learning computer programming

Basic knowledge of programming helpful