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Data Science in 8 Minutes | Data Science for Beginners | What is Data Science? | Edureka
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This Edureka video on "What is Data Science" will introduce you to the concepts of Data Science and how it is used to solve real-world problems. You will learn Data Science with an example on UBER dataset. Data science is the process of using the data to find solutions / to predict outcomes of a problem statement. Below are the topics covered in this Data Science Tutorial:
0:57 What is Data Science?
1:11 How Data Science works? : Data Science at UBER
2:06 Data Science Process
a. Business Requirements
b. Data Collection
c. Data Cleaning
d. Data Exploration and Analysis
e. Data Modelling
f. Data Validation
g. Deployment and Optimization
4:17 Data Science Applications
6:05 Who is a Data Scientist?
6:18 Data Scientist Job Trends
6:51 Data Scientist Skills
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#edureka #DataScienceEdureka #whatisdatascience #Datasciencein8minutes #Datasciencecourse #datascience
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About the Master's Program
This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles.
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Topics Covered in the curriculum:
Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc.
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0:57 What is Data Science?
1:11 How Data Science works? : Data Science at UBER
2:06 Data Science Process
a. Business Requirements
b. Data Collection
c. Data Cleaning
d. Data Exploration and Analysis
e. Data Modelling
f. Data Validation
g. Deployment and Optimization
4:17 Data Science Applications
6:05 Who is a Data Scientist?
6:18 Data Scientist Job Trends
6:51 Data Scientist Skills
Subscribe to our channel to get video updates. Hit the subscribe button above.
#edureka #DataScienceEdureka #whatisdatascience #Datasciencein8minutes #Datasciencecourse #datascience
- - - - - - - - - - - - - -
About the Master's Program
This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles.
- - - - - - - - - - - - - -
Topics Covered in the curriculum:
Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc.
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