Python , R programming for Data Science : Absolute Beginners
- Description
- Curriculum
- FAQ
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The course is packed with real life projects examples
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Get Transformed from Beginner to Expert .
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Become expert in using Python Pandas,NumPy libraries ( the most in-demand )
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Become expert in R programming.
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Source Codes are provided for each session in Python so that you can practise along with the lectures..
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Start doing the extrapolatory data analysis ( EDA) on any kind of data and start making the meaningful business decisions
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Start python and R programming professionally
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Extract data from various sources like websites, pdf files, csv and RDBMS databas
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Start using the highest in-demand libraries used in Data Science / Data Analysis project : Pandas , NumPy ,ggplot
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Start making visualizations charts – bar chart , box plots which will give the meaningful insights
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Learn the art of Data Analysis , Visualizations for Data Science Projects
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Learn to play with SQL on R and Python Console.
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Integrate RDBMS database with R and Python
Real world Case Studies Include the analysis from the following datasets
1. Melbourne Real Estate ( Python )
2. Market fact data.( Python )
3. Car Datasets( Python )
4. Covid 19 Datasets( Python )
5. Uber Demand Supply Gap ( R )
6. Bank Marketing datasets ( R )
7. Investment Case Study (Excel)
8. Market fact data.( SQL)
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16
If else Conditions - Decisions Making -
17
Testing you Decision Making Skills (If elif If ) -
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Python Loops- Intro
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19
Understanding For and While Loop
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20
Python Comprehensions-Intro
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21
Comprehension ; Loops in List,Dictionary
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22
Python Function-Intro
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23
Understanding Python Function
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24
Map,Reduce,Filter -Introduction
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25
Map,Reduce ,Filter -Using Lambda Functions
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26
Assignment-Map Reduce Filter
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44
Introduction to the world of Visualisation
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45
Types of Plots
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46
Matplotlib Basics
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47
Matplotlib-Marketing Data Plots ( Boxplots,Histograms,Scatter)
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48
Searborn-Basics - Beautify the plots ( Boxplots,histograms,scatter )
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49
Seaborn-Correlation Matrix
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50
Aggregators Plots ( Bi-variate Analysis ) - Bar Charts , Boxplots , Histograms
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51
Timeseries Plots - Heatmap Plots
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59
Introduction to the Course - R
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60
Installation of R and R Studio
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61
Understanding R Studio
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62
Understanding Datatypes in R
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63
Crash Course in R - 1
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64
Basics of R - 1
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65
Crash Course in R - 2
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66
Crash Course in R - 3
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67
Introduction to Vectors
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68
Vectors in R - 1
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69
Vectors in R - 2
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70
Vectors
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71
Factors in R -1
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72
Factors in R -2
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73
Factors
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74
Introduction to Matrices
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75
Matrices
