Description
Curriculum
Instructor
Learn how to use Python for Data Science, Machine Learning & Data Analysis, Learn Hand’s on Pandas and NumPy With 100+ Exercises and 4 Real Life Projects !
On Completion of this course, you’ll be a specialist in the following concepts & processes:
- Pandas Data Structures: Series, DataFrame and Index Objects
- Essential Functionalities
- Data Handling
- Data Pre processing
- Data Wrangling
- Data Grouping
- Data Aggregation
- Pivoting
- Working With Hierarchical Indexing
- Converting Data Types
- Time Series Analysis
- Advanced Pandas Features
This course is just apt for you in case you’d want to be a pro:
- Coding with Pandas toolkit
- Hundreds of methods and attributes across numerous pandas objects
- Manipulating data quickly and efficiently
- Creating data frames with pandas and Recognizing analytical approaches to data
- Building a Solid Foundation in Data Analysis with Python
Target Enrollers of this course:
- Data Analysis Beginner
- Business and Analyst
- Students and Other Professionals
- Beginner Python developers Curious to learn about Data Science
- Aspiring data scientists who want to add Python to their tool arsenal
- Any curious learner who wants to update their knowledge in Business Analysis
- AI and ML aspirants to upgrade their knowledge in Data Preprocessing before applying the machine learning algorithms to their projects
Some exceptional benefits associated with this course enrolment are:
- Quality course material on Data Analysis and Data Science
- Lifetime access to the course
- Instant & free course updates
- Access to all Questions & Answers initiated by other students as well
- Personalized support from the instructor’s end on any issue related to the course
- Few free lectures for a quick overview
It’s time for you to grab the opportunity and make the most out of this course.
Enroll today!!
Curriculum
- 13 Sections
- 103 Lessons
- 15 Hours
Expand all sectionsCollapse all sections
- Section 1: Getting Started7
- 1.1Course Introduction4 Minutes
- 1.2How To Get Most Out Of This Course2 Minutes
- 1.3Better To Know These Things3 Minutes
- 1.4How to Install Python Ipython And Jupyter Notebook9 Minutes
- 1.5How To Install Anaconda For Macos And Linux Users7 Minutes
- 1.6How To Work With The Jupyter Notebook Part 116 Minutes
- 1.7How To Work With The Jupyter Notebook Part 211 Minutes
- Section 2: Pandas Building Blocks2
- Section 3: Pandas Data Structures4
- Section 4: Data Indexing And Selection7
- 4.1Data Selection In Series Part 16 Minutes
- 4.2Indexers Loc And Iloc In Series12 Minutes
- 4.3Data Selection In Series Part 22 Minutes
- 4.4Data Selection In Dataframe Part 24 Minutes
- 4.5Theory On Data Indexing And Selection6 Minutes
- 4.6Accessing Values Using Loc Iloc And Ix In Dataframe Objects9 Minutes
- 4.7Data Selection In Dataframe Part 15 Minutes
- Section 5: Essential Functionalities11
- 5.1How To Reindex Pandas Objects12 Minutes
- 5.2How To Drop Entries From An Axis8 Minutes
- 5.3Arithmetic And Data Alignment7 Minutes
- 5.4Arithmetic Methods With Fill Values15 Minutes
- 5.5Broadcasting In Pandas7 Minutes
- 5.6Apply And Applymap In Pandas8 Minutes
- 5.7How To Sort And Rank In Pandas13 Minutes
- 5.8How To Work With The Duplicated Indices4 Minutes
- 5.9Summarisig And Computing Descriptive Statistics7 Minutes
- 5.10Unique Values Value Counts And Membership12 Minutes
- 5.11Theory On Essential Functionalities10 Minutes
- Section 6: Data Handling6
- Section 7: Data Cleaning And Preparation15
- 7.1How To Handle Missing Values9 Minutes
- 7.2How To Filter The Missing Values9 Minutes
- 7.3How To Filter The Missing Values Part 29 Minutes
- 7.4How To Remove Duplicate Rows And Values12 Minutes
- 7.5How To Replace The Non Null Values9 Minutes
- 7.6How To Rename The Axis Labels7 Minutes
- 7.7How To Descretize And Bin The Data22 Minutes
- 7.8How To Filter And Detect The Outliers4 Minutes
- 7.9How To Reorder And Select Randomly7 Minutes
- 7.10Converting The Categorical Variables Into Dummy Variables10 Minutes
- 7.11How To Use _map_ Method7 Minutes
- 7.12How To Manipulate With Strings13 Minutes
- 7.13Using Regular Expressions20 Minutes
- 7.14Working With The Vectorized String Functions9 Minutes
- 7.15Theory On Data Preprocessing11 Minutes
- Section 8: Data Wrangling10
- 8.1Hierarchical Indexing-18 Minutes
- 8.2Hierarchical Indexing Reordering And Sorting-27 Minutes
- 8.3Summary Statistics By Level-33 Minutes
- 8.4Hierarchical Indexing With Dataframe Columns-45 Minutes
- 8.5How To Merge The Pandas Objects-120 Minutes
- 8.6Merging On Row Index-213 Minutes
- 8.7How To Concatenate Along An Axis-319 Minutes
- 8.8How To Combine With Overlap-47 Minutes
- 8.9How To Reshape And Pivot Data In Pandas-59 Minutes
- 8.10Theory On Data Wrangling8 Minutes
- Section 9: Data Grouping And Aggregation7
- 9.1Groupby Operation16 Minutes
- 9.2How To Iterate Over Groupby Object6 Minutes
- 9.3How To Select Columns In Groupby Method3 Minutes
- 9.4Grouping Using Dictionaries And Series3 Minutes
- 9.5Grouping Using Functions And Index Level5 Minutes
- 9.6Data Aggregation10 Minutes
- 9.7Thoery On Data Group by And Aggregation4 Minutes
- Section 10: Time Series Analysis8
- 10.1Introduction To Time Series Data Types10 Minutes
- 10.2How To Convert Between String And Datetime15 Minutes
- 10.3Time Series Basics With Pandas Objects13 Minutes
- 10.4Date Ranges Frequencies And Shifting Part 111 Minutes
- 10.5Date Ranges Frequencies And Shifting Part 211 Minutes
- 10.6Time Zone Handling9 Minutes
- 10.7Periods And Period Arithmetics11 Minutes
- 10.8Thoery On Time Series Analysis6 Minutes
- EXERCISE VIDEOSHere you will get practical knowledge with respect to all the lessons you have learnt so far.16
- 11.1Practice Part 14 Minutes
- 11.2Practice Part 1 Solution22 Minutes
- 11.3Practice Part 23 Minutes
- 11.4Practice Part 2 Solution13 Minutes
- 11.5Practice Part 33 Minutes
- 11.6Practice Part 3 Solution17 Minutes
- 11.7Practice Part 43 Minutes
- 11.8Practice Part 4 Solution15 Minutes
- 11.9Practice Part 52 Minutes
- 11.10Practice Part 5 Solution15 Minutes
- 11.11Practice Part 61 Minute
- 11.12Practice Part 6 Solution6 Minutes
- 11.13Practice Part 73 Minutes
- 11.14Practice Part 7 Solution13 Minutes
- 11.15Practice Part 83 Minutes
- 11.16Practice Part 8 Solution12 Minutes
- PROJECT VIDEOSThis section is related to projects on Padas and you will be able to work with the Industry oriented standard projects to analyse the data. Once you finish this section you'll be able to handle the projects on your own.9
- 12.1A Brief Introduction To The Pandas Projects11 Minutes
- 12.2Project 1 Description5 Minutes
- 12.3Project 1 Solution Part 117 Minutes
- 12.4Project 1 Solution Part 214 Minutes
- 12.5Project 2 Description2 Minutes
- 12.6Project 2 Solution Part 119 Minutes
- 12.7Project 3 Description3 Minutes
- 12.8Project 3 Solution Part 112 Minutes
- 12.9Project 3 Solution Part 212 Minutes
- RESOURCE FILES1
Pruthviraja L
1 Student2 Courses
Hi, I am Pruthviraja L, with over 7 years of teaching and training experience from various technical institutes. I'm a Certified Data Analyst holding valuable certifications from various eLearning centers including Udemy, Intellipaat-Bengaluru, LinkedIn eLearning center, etc.
My skillset includes Matlab, Python, SAS, R , AI and Machine learning, Data Science and Data Analysis.
I'm a multi faceted software professional aspirant with demonstrated capability in deploying analytical and programming methodologies to extract insights for boosting and bolstering user requirements. Pro at conducting statistical analysis and data modeling for transforming raw data into actionable strategies.
Regarded as the author of the book - 'Elements of Electrical Engineering' under the publication of 'I.K. International Publishing House Pvt Ltd', New Delhi, India, easily available in many countries including the USA and UK via Amazon and many other seller portals.
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