Complete Python & Data Analytics – Beginner to Advanced

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Learn Python Programming, Data Analysis & Wrangling with Pandas, Data Visualization and Machine Learning.
What you'll learn
Python coding - from Zero to Hero
Realistic Data analysis and wrangling with Pandas
Reshaping, merging, joining, and all sorts of complex data manipulations
Handling Missing Values
Groupby Operations (with Finance applications)
Time Series Resampling
Complex Rolling Windows Operations
OLS Linear Regressions
Logistic Regressions
Linear Discriminant Analysis
Neural Networks
Principal Component Analysis (PCA)
Support Vector Machines
K-Nearest Neighbors Algorithm
K-Means Clustering
Professional data visualization with Seaborn
Real-World Applications in Finance, Image/Facial Recognition, etc
Requirements
No programming experience is required. You will learn everything you need to know about Python, data analytics and machine learning in this course.
Intermediate-level coders can directly proceed to Part 2 (Data Analytics with pandas)
Description
This course is a complete guide on Python & data analytics. You will learn everything they need to know to conduct data analysis and carry out data science using Python.In particular, this course consists of 4 major parts ("mini-courses"):Python Crash Course for BeginnersAll essential data types and common operationsComprehensive string manipulationsControl flowsLists, Tuples and SetsDictionariesObject-Oriented ProgrammingInheritanceDatetimeModules and PackagesExceptions Handling, etcA Comprehensive Course on Data Analysis and Manipulation using PandasSeries and Data FramesIndexing, filtering, sorting, counting, etcAggregation vs TransformationGroupbyReshape the data, pivot/meltmerge/join missing valuesapply, mapTime series computations & resamplingRolling windowsVectorized string and date/time manipulations, and many moreA Complete Course on Data Visualizationpandas & seaborn15+ Types of Plots (relational, statistical, categorical)Multi-plots with "facets", etc.An Applied Machine Learning Course using SciKit-Learn Linear RegressionsLogistic RegressionsLinear Discriminant AnalysisPrincipal Component AnalysisK-MeansK-Nearest NeighborsSupport Vector MachinesNeural NetworksHyper-parameters TuningFacial RecognitionHand-written Digits Recognition, etcThe course is one of the most comprehensive and detailed course ever on the Pandas package. It highlights the complexity of data wrangling which occupies about 80% of data scientists' time, and gives you a solid foundation to meet the challenging requirements of handling messy real-world data. This course also introduces 8 most common ML algorithms and their applications in practical tasks such as image recognition and classifications. The focus is on applications and intuitive understanding rather than the underlying theories and mathematics. By the end of this course, you will not only become a competent Python programmer, but also a skilled data analyst ready to take on real-world projects.
Who this course is for
Absolute Beginners
Intermediate-level Python coders who wants to level up their data analytics skills using Pandas and Machine Learning tools.
All aspiring data scientists, data analysts and data engineers
Finance and business professionals/students ( marketing, management, etc)
Anyone who is curious about Python coding and/or data analytics
Homepage

https://www.udemy.com/course/complete-python-data-analytics-beginner-to-advanced/

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