Level 1 : Hands-on Python for Data Science

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32 Hours

Course offered by DataScienceLab

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What is this course about?

This course focuses on python for data science. You will learn about Python programming interfaces, how data stored and referred how to import various data formats in Python. Additionally, you will learn few advanced programming tasks using Python.

You will learn various data explorations tasks through pandas and NumPy libraries and to visualize data using Matplotlib library.

Data received or gathered is not always clean. There are many challenges faced to deal with the messy data. Before you start with analysis, it is important to take care of missing values, outliers, incorrect values. Also, it is essential to make data in proper format.

Once the data is explored and detected for anomalies, it needs to be corrected. You learn most used data cleansing tasks.

Duration: 32 hours

Who Should Attend?

Pre-requisite: This program assumes you have sound knowledge in basic statistics.

This is a level one program. Anyone who wants to enter into analytics/ data science or R/SAS data science programmer who wants to enrich with one more programming language.

What to bring ?

You must bring your own laptop, 64 bit, at least i3 core processor (i5 preferred). Instructions on installation of anaconda for Python would be sent you before the workshop. You need to follow those instructions to make your laptop ready before the class.

Methodology :

This is a complete hands on course. There would be lots of assignments, exercises and capstone project at the end of the course.

Also, you would achieve in house certification at the end of the course once you pass the tests and complete your capstone project.

About the Trainer

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DataScienceLab

MSc in Statistics,three SAS Global Certifications

Preeti Ranadive Pandhu received her Bachelor of Science in Applied (Industrial) Statistics degree from University of Pune in 1995 and then she completed her Master of Science in Applied (Industrial) Statistics , Pune University University. She cleared Ph.D. entrance exam (Dept. of Statistics ) and attended first 6 months courseware and 6 months of work for Ph.D. her Research area is spatial data mining
She is SAS certified Base and Advanced Programmer for SAS 9 as well as Predictive Modeler Using SAS Enterprise Miner 7
She has more than 18 years of experience in analytics and training. Teaching is her passion and teaching complex concepts by making them simple is her expertise. Has extensive knowledge and innovative style of teaching that have made her popular among students.
She has mentored hundreds of professionals achieve SAS certifications . She conducts corporate trainings for leading local and international companies on analytics , SAS and R.
She started her career as a lecturer for statistics and her journey into the corporate world with IDeaS (now a SAS company), managed team of Business analyst in a optimization and forecasting domain , later on joined SAS to try her hand on corporate training and manage learning and develop function. Subsequently stepped back into analytics domain to contribute in solution testing team and research /consulting team, she has handled different roles and functions effectively . She was with SAS for overall 9 years.

At Data Science Lab, she not only trains but also mentors professionals as well as students who wants to make solid career or career shift into analytics.
She has assisted and done technical reviews for two books on analytics and data visualization using SAS for US publication. One of them is written by well know author in SAS world from UK.