Lets us know your experience, it will help others.
Starting from Sep 26th, 2020
10:00 am – 1:00 pm
You Save Rs. 16000/-
Data Analytics is a process of examining, cleaning, manipulating, transforming and generating information from the data. Now a days in Business world data analytics plays a vital role to form decisions more scientifically and help to increase operational effieciency.
Top skill in demand now a days is to process raw data into business insights. There is no special programming language dedicated to data science but looking at the exciting features of the python language you can make your mind. Python has great features like fast and high computational capability, extremely compatible, cross platform support , distributed computing and vector arithmetic. In this course we will learn python programming, statistics and analytics used for business analytics. We will learn data wrangling, data cleansing as well as data visualization using popular Python libraries like Numpy, Pandas, Matplotlib, and seaborn. In this course you will get to learn apply exploratory data analytics the essential part of data analytics.
By the end of this you will be able to extract, read and write data from csv files, data cleansing, data manipulation, data visualization, run inferential statistics, understand the business problems, based on problems you will be able to select and apply machine learning models and deploy it.
Data Analytics is meant for all and everyone should go for this, learn to play with data and grasping required skills isn’t just valuable, its essential now. Does not matter from which field you – economics, computer science, chemical, electrical, are statistics, mathematics, operations you will have to learn this.
|Random Variables||1 Lecture||25:00|
|Probability Distribution||1 Lecture||21:00|
|Central Limit Theorem||1 Lecture||25:00|
|Confidence Intervals||1 Lecture||25:00|
|Hypothesis Testing||1 Lecture||25:00|
|Chi Square Test||1 Lecture||25:00|
|Anova Test||1 Lecture||25:00|
|Basic statistics using data examples||1 Lecture||30:00|
|Central tendencies||1 Lecture||43:00|
|Correlation analysis||1 Lecture||34:00|
|Data Summarization||1 Lecture||40:00|
|Data Dictionary||1 Lecture||29:00|
|Outliers /Missing Values||1 Lecture||30:00|
|Basic Linear Algebra – dot product, matrix multiplication and transformations||1 Lecture||38:00|
|The Python Ecosystem||1 Lecture||15:00|
|Why Python over R/SAS||1 Lecture||10:00|
|What to expect after you learn Python||1 Lecture||35:00|
Understanding and choosing between different Python versions
|Setting up Python on any machine (Windows/Linux/Mac)||1 Lecture||24:00|
Using Anaconda, the Python distribution
Exploring the different third-party IDEs (PyCharm, Spyder, Jupyter, Sublime)
Setting up a suitable Workspace
Running the first Python program
Interactive Mode/ Script Mode Programming
Identifiers and Keywords
Single and Multi-line Comments
Data Types in Python (Numbers, String, List, Tuple, Set, Dictionary)
Implicit and Explicit Conversions
Understanding Operators in Python
Working with various Date and Time formats
Working with Numeric data types – int, long, float, complex
String Handling, Escape Characters, String Operations
Working with Unicode Strings
Local and Global Variables
Flow Control and Decision Making in Python
Understanding if else conditional statements
Working in Iterations
Understanding the for and while Loop
Loop Control Statements– break, continue, pass
Understanding Dictionary- The key value pairs
List Comprehensions and Dictionary Comprehensions
Functions, Arguments, Return Statements
Packages, Libraries and Modules
Error Handling in Python
Reading data from files (TXT, CSV, Excel, JSON, KML etc.)
Writing data to desired file format
Creating Connections to Databases
Working in Iterations
Importing/Exporting data from/to NoSQL databases (MongoDB)
Importing/Exporting data from/to RDBMS (PostgreSQL)
Getting data from Websites
Manipulating Configuration files
Introduction to Data Wrangling Techniques
Why is transformation so important
Understanding Database architecture – (RDBMS, NoSQL Databases)
Understanding the strength/limitations of each complex data containers
Understanding Sorting, Filtering, Redundancy, Cardinality, Sampling, Aggregations
Converting from one Data Type to another
Introduction to Numpy and its superior capabilities
Understanding differences between Lists and Arrays
Understanding Vectors and Matrices, Dot Products and Matrix Products
Universal Array Functions
Understanding Pandas and its architecture
Getting to know Series and DataFrames, Columns and Indexes
Getting Summary Statistics of the Data
Data Alignment, Ranking & Sorting
Combining/Splitting DataFrames, Reshaping, Grouping
Identifying Outliers and performing Binning tasks
Cross Tabulation, Permutations, the apply() function
Introduction to Data Visualization
Line Chart, Scatterplots, Box Plots, Violin Plots
Hi I am Kushal Dwivedi and I am super excited that you are reading this.
Professionally, I am a data science management consultant with over 8+ years of experience in Banking, Capital Market, CCT, Media and other industry. I was trained by best analytics mentor at dunnhumby and now a days I leverage Data Science to drive business strategy, revamp customer experience and revolutionize existing operational processes.
From this course you will get to know how I combine my working knowledge, experience and qualification background in computer science to deliver training step by step.
It was a great experience of learning in palin analytics. The course content and the lecture delivery is quite good. It is totally hands-on learning and very satisfactory learning. The main thing I found in palin is, this organization is very supportive and you can reach out any time for your queries. I would like to reach out here for further courses and will recommend for a better learning place
One of the nice institutes in Delhi NCR, they do provide awesome training. I have seen in previous comments/reviews that Palin Institute do not provide demo classes but this is totally wrong they do send class recordings and as well as they ask you to attend a demo class as well to get a clear view on the classes.
Thank you Monojay…Best of Luck for your bright future.
Took a weekend batch. The trainer is good . Has excellent knowledge of the concepts, liked his teaching style. Recommended.
Add Reviews about your experience with us.
Data Analytics includes different processes like data gathering, data wrangling, data preprocessing, statistics, data visualization. The mandate steps are Data preprocessing -> Data Visualization -> Exploratory Data Analysis
Pool of working professionals with several years experience in same field with different domains like banking, healthcare, retail, ecommerce and many more.
Along with the high quality training you will get a chance to work on real time projects as well, with a proven record of high placement support.
We will cover SQL for data gathering, Python programming, Data Analytics, Statistics, Data Visualization.
Its Live interactive training, Ask your quesries on the go, no need to wait for doubt clearing.
you will have access to all the recordings, you can go through the recording as many times as you want.
Ask your questions on the go or you can post your question in group on facebook, our dedicated team will answer every query arises.
Yes we will help learners even after the subscription expires.
No you cannot download the recording it will be in your user access on LMS, you can go through at any point of time.
During the training and after as well we will be on the same slack channel, where trainer and admin team will share study material, data, project, assignment.
you can write your questions at email@example.com we will address your questions there.
Lets us know your experience, it will help others.