vc_rowvc_columnvc_row_innervc_column_innervc_column_text One of the best practices used in today’s data science is exploratory data analysis (EDA). Individuals usually don’t know the difference between data analysis …

Course Access

6 months

Last Updated

March 2, 2021

Students Enrolled


Total Video Time

18 hours, 18 minutes

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One of the best practices used in today's data science is exploratory data analysis (EDA). Individuals usually don't know the difference between data analysis and exploratory data analysis before beginning a career in data science. The difference between the two is not very large, but both have different functions. Exploratory data analysis is a supplement to inferential statistics, with laws and formulas preferring to be quite static. At an advanced stage, EDA involves looking at the data set from various angles and explaining it and then summarizing it. Data visualization is used by EDA in Python to draw concrete patterns and observations. It also includes the preparation of data sets for review by the removal of data irregularities. Based on EDA results, business decisions are often taken by businesses, which can have consequences later on. Takshila Learning has an advanced EDA with Python which ensures that you learn perfectly and later on take it to the standard applications in the related industry. After completing the advanced level program with us, you will be writing programs that ask Internet APIs for data by the end of the specialization and extract valuable information from them. And by reading the documentation, you will be able to learn to use new modules and APIs on your own. That will give you a fantastic opportunity to be an independent Python programmer. The dictionary data structure and user-defined functions are introduced in this course by us. You will also learn about local and global variables, parameter-passing choices and keywords, named functions, and lambda expressions.  

What is included in Our Python for Advanced EDA Course?

• Fundamentals of Python • Data visualization using Seaborn Matplotlib • Actual practical use cases like credit risk analysis and zomato delivery analysis. • OOPS concepts and Exception Handling • Python Plotly and Python Cufflinks • Detailed PDFs complimenting the video lectures. • Faculty support via Whatsapp, Con-call • Doubt sessions – Via Whatsapp, Con-call, Webinar • Interview Support - We will be providing you with Interview questions and also conducting mock interviews to give you a definitive edge over the rest of the crowd.    
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Demos For Advanced EDA with Python Course

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  • Validity: 3 Months / 6 Months
  • No. of videos: 50+ hours
  • Certificate: Certificate from Takshila Learning
  • Interview Support: We will be providing you with Interview questions and also conducting mock interviews to give you a definitive edge over the rest of the crowd.
  • Language: Bilingual(Hindi + English)
  • Mode of Delivery: Pen drive, Online Classes
  • Queries/Problems Solution: via Online Discussion Forums, Live Chat with Faculty, and over Phone Calls.

Career Opportunities for Python Programmers:

• EDA Engineer • Python Developer • Research Analyst • Data Analyst • Data Scientist • Software Developer • DevOps Engineer • Web developer • Learn HTML, JavaScript, CSS, and Django to become a full-time web stack developer. • Learn Machine learning after this course • Use SciPy, NumPy, and Django in the BFSI sector to display sophisticated calculations.  

About the Faculties:

Takshila Learning combined 24+ years of experience in Machine learning, data analysis, and Financial data analytics for this Python for EDA Course prepared by- • Nitin Joseph - certified by IMA Bangalore chapter for RPA and Machine learning in Finance and accounting. • Munmun Ghosal - She is working as a Data Scientist and trainer. She has a total of 9 years of work experience in academics and industry with research areas in Data Analytics, Machine Learning, VLSI, and Signal processing. She is passionate about learning and sharing knowledge, innovation, programming, writing technical blogs. She delivers corporate and onsite training at various industries and Management/Engineering Colleges. She has worked on various projects on Data Analytics, Machine learning and AI,  IoT, VLSI, and Signal processing. Her skill set includes R, Python, Tableau, Power BI, VHDL, VERILOG, C Language, C++, Excel, MATLAB, Virtuoso ADE of CADENCE (45 nm), Xilinx ISE, Aldec’s Active HDL, and Microwind. She has presented and published research papers in several reputed national /international journals and conferences. She has completed her M. Tech (VLSI) and B.E. (Electronics Engineering).Hemant Singh - B.Tech in Computer Science and Engineering(Specialization in Data Analytics). Trains college students and industry professionals specifically on data science. 1-years Experience in Data Analytics

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FAQ Of Python Course

  1) What is Python? What are the benefits of using Python?
Python is a high-level, interpreted and general-purpose dynamic programming language that focuses on code readability. The syntax in Python helps the programmers to do coding in fewer steps as compared to Java or C++. The language founded in the year 1991 by the developer Guido Van Rossum has the programming easy and fun to do. The Python is widely used in bigger organizations because of its multiple programming paradigms. They usually involve imperative and object-oriented functional programming. It has a comprehensive and large standard library that has automatic memory management and dynamic features   2) What Is Python Used For? Python is widely used in Artificial Intelligence, Machine Learning, Neural Networks and other advanced fields of Computer Science. One can use python for the following: • System programming • Graphical User Interface Programming • Internet Scripting • Component Integration • Advance Analytics • Model Building • Artificial Intelligence • Machine Learning • Database Programming • Gaming, Images, XML , Robot and more   3) How Long Does It Take to Learn Python? With the proper time and dedication, you can learn Python in just a few months. Like any skill, how quickly you learn Python is ultimately dependent on how much time and effort you put in. It’s because all of us possess unique abilities and tend to perform differently in different mental tasks. And hence, the learning curve could be shorter for some and longer for many. Anyways, coming to the point, Python is a very simple, elegant, and type free programming language. So, it’s relatively easy to learn. However, you can see it from three different levels. 1. Elementary Python 2. Advanced Python 3. Professional Python Basic Python is where you get to learn syntax, keywords, if-else, loops, data types, functions, classes and exception handling, etc. An average programmer may take around 6–8 weeks to get acquainted with these basics.   4) Why Python and how popular is it for Data Science? The most alluring factor of Python is that anyone aspiring to learn this language can learn it easily and quickly. When compared to other data science languages like R, Python promotes a shorter learning curve and scores over others by promoting an easy-to-understand syntax.   5) What does a Data Scientist do? Data scientists work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals. They design data modeling processes, create algorithms and predictive models to extract the data the business needs, then help analyze the data and share insights with peers.   6) Which companies use Python? Many companies use python these days. The top tier companies using Python are as follows Google - Python is in their top 3 alongside C++ and Java • Amazon - the machine learning engine is powered by Python • Microsoft - Python used for data science and analytics • Facebook - Python helps in maintaining and managing FB infrastructure • Instagram -Instagram moved to Python 3 is just great example of a gigantic tech company using python in combination with Django. Instagram has about 400M of daily active users who share more than 95M photos & videos. Instagram choose Python because of its simplicity & popularity. • IBM -IBM uses Python for its factory tool control applications. • Spotify - Python used for backend and data analysis • Netflix - Python used for machine learning and marketing recommendations (and many others) • Uber - at the lower level backend, the engineers work mostly in Python, Node.js, Go and Java • Walt Disney Feature Animation-It uses Python as a scripting language for animation. All the magic that happens in Disneyland has a bit of Python behind it. • Yahoo! Maps - It uses Python in many of its mapping lookup services & addresses. Survey Monkey- Survey Monkey use Python were its simplicity, tons of libraries allowing to build Web Apps faster, as well as facilitating working with deployment, Unit Testing, etc. • YouTube - Python has been the driving force behind YouTube, used by millions for downloading & uploading videos of all hues and sizes. YouTube has been coded in a way which makes it easier & extremely interactive for the user. • Quora- Quora is a portal where you get your answers. Quora’s language programming has been developed using Python’s framework. • Dropbox - Many of our choices to store our data are going online. We create a document, we save it & we share it. It is the ideal way to preserve your documents online. This file hosting has been created by using Python. • Reddit- It is a place where you can find a lot of information & entertainment across thousands of categories. Popularly called internet’s front page has been developed by using Python. • Bitly- The popular link management platform created by Peter Stern in 2008 shortens close to 600 million links annually. This website also owes greatly to Python as it came into existence because of Python. • Nokia- Nokia make uses of Python for S60 and also Python for Maemo for its S60 & Maemo software platforms. • NASA- The NASA uses Workflow Automation System, an application written & developed in Python. It also uses Python for Astronomy Picture of the Day, API, PyMDP Toolbox, Everest, PyTransit.   7) What do I need to start with Python for a Data Science course? • A working laptop / desktop with 4 GB RAM • Internet connection   8) I am familiar with a few Programming Languages like C++/PHP/. Will it help me in learning Python? Yes, definitely. But even if you are new to any programming language , You can learn python easily.   9) Are there copyright restrictions on the use of Python? You can do anything you want with the source, as long as you leave the copyrights in and display those copyrights in any documentation about Python that you produce. If you honor the copyright rules, it’s OK to use Python for commercial use, to sell copies of Python in source or binary form (modified or unmodified), or to sell products that incorporate Python in some form. We would still like to know about all commercial use of Python, of course.   10) Why is it called Python? Python was invented by Guido van Rossum in the Netherlands, in early 90s. Guido Van Rossum is fan of ‘Monty Python’s Flying Circus’, a famous TV show in Netherlands When he began implementing Python, Guido van Rossum was also reading the published scripts from “Monty Python’s Flying Circus”, a BBC comedy series from the 1970s. Van Rossum thought he needed a name that was short, unique, and slightly mysterious, so he decided to call the language Python.   11) What are the key features of Python? • Interactive • Interpreted • Modular • Dynamic • Object-oriented • Portable • High level   12) What are the drawbacks of Python? • Difficulty in using other languages • Weak in mobile Computing • Run-Time errors • Underdeveloped   13) What Course material i will get with this course. • Detailed Syllabus • Recorded Sessions covering concepts and practical. • Pdf’s with detailed explanation of the respective videos. • Python files for reference • Assignments/ Problem Statements/ Interview Questions
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Course Currilcum

    • Video and PDF/HTML file for Introduction to Python 00:30:00
    • Video and PDF/HTML file for Installation of Python 00:10:00
    • Video and PDF/HTML file 00:30:00
    • Video and PDF/HTML file for Operators 00:15:00
    • Video and PDF/HTML file for Range Function 00:10:00
    • Video and PDF for Conditional Statement and Comparators 00:11:00
    • Video and PDF for IF-Statement 00:09:00
    • Video and PDF for IF-ELIF-ELSE Statement 00:08:00
    • Video and PDF for IF-ELIF-ELSE Statement 00:08:00
    • Video and PDF for Nested – IF Statement 00:09:00
    • Video and PDF for For loop 00:08:00
    • Video and PDF for While 00:10:00
    • Video and PDF for Break and Continue 00:10:00
    • Video and PDF for Continue 00:10:00
    • Video and PDF for String 00:07:00
    • Video and PDF for String manipulation 00:30:00
    • Video and PDF for List 00:07:00
    • Video and PDF for List Comprehension 00:40:00
    • Video and PDF for Tuple 00:05:00
    • Video and PDF for Tuple Operations 00:10:00
    • Video and PDF for Dictionary 00:05:00
    • Video and PDF for Dictionary Comprehension 00:30:00
    • Video and PDF for Set 00:07:00
    • Video and PDF for Set Operations 00:15:00
    • Video and PDF for Python Function 00:17:00
    • Video and PDF for Map Function 00:10:00
    • Video and PDF for Reduce Function 00:10:00
    • Video and PDF for Filter Function 00:11:00
    • Video and PDF for lambda Function 00:06:00
    • Video and PDF for Reading and Saving file as .CSV and Text 00:10:00
    • Video and PDF for Reading and Saving file as .XLSX 00:05:00
      • Video and PDF for Basic Statistics 01:00:00
      • Video and PDF for Python Numpy 01:10:00
      • Video and PDF for Python Pandas 01:10:00
      • Video and PDF for Python Matplotlib 01:00:00
      • Video and PDF for Data Visualisation with Matplotlib 01:00:00
        • Video and PDF for Seaborn, Data Visualisation with Seaborn 01:10:00
        • Video and PDF for EDA Explaination 00:30:00
        • Video and PDF for Use Case-1 on Zomato Dataset 01:00:00
        • Video and PDF for Use Case-2 on Bike-Sharing Dataset 01:00:00
        • Video and PDF for Use Case-3 on Bank Marketing Data 01:00:00
        • Video and PDF for Use Case-4 on Bank Risk Detection 01:00:00
        • Video and PDF for Use Case-5 on Credit card Fraud Data 00:35:00

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      Takshila Learning https://www.takshilalearning.com/course/advanced-python-course-google-cpc-camp Advanced EDA with Python Course – Exploratory Data Analysis