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Data Science and Big Data Analytics

Explore the Power of Data: Analyze & Predict!

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  • Nevyžaduje praxi

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Who is the course for

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Who is this course for?

The "Data Science and Big Data Analytics" course is designed for individuals eager to dive into the world of data and develop hands-on skills in data analysis, machine learning, and big data technologies. Whether you're a beginner looking to start a career in data science or a professional aiming to enhance your data handling capabilities, this course offers the foundational knowledge and practical skills needed to handle real-world data challenges effectively.

This course is particularly beneficial for those who aim to understand the vast amounts of data that their businesses generate and to leverage this data for decision-making and strategic planning. It provides the tools and techniques to analyze big data and delivers insights into how data science can drive business value.

Target audience:

  • Aspiring data scientists and analysts

  • IT professionals looking to transition into data roles

  • Business analysts and managers who need to understand data trends

  • Software developers interested in building data-driven applications

  • Marketing professionals seeking to leverage customer data for strategic insights

  • Graduate students in fields requiring data analysis skills

What will you learn

More information
  • Data mining techniques
  • Predictive modeling
  • Big data tools proficiency
  • Statistical analysis skills

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This course can be customized - either as an individual training 1:1 or for your team. Just leave us your contact and we will contact you with options tailored to your needs.

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Timeline

Week 1

– Intro to Big Data Analytics and Data Analytics Lifecycle
  • Big Data Characteristics
  • Business Value from Big Data
  • Data Scientist
  • Intro to Data Analytics Lifecycle
  • Conclusion (Lifecycle Continuation)
  • Lab: Intro to the Lab Environment

Week 2

– Basic Data Analytics Methods Using R
  • Intro to R Programming Language
  • R Studio Demo
  • Lab: Intro to R Programming
  • Analyzing and Exploring Data
  • Lab: Basic Statistics, Visualization and Hypothesis Testing

Week 3

– Advanced Analytics Theory and Methods, Part 1
  • Intro to Advanced Analytics Theory and Methods
  • K-Means Clustering: Algorithm, Use Case, Diagnostics
  • Lab: K-Means Clustering
  • Association Rules: Algorithm, Use Cases, Diagnostics
  • Lab: Association Rules
  • Linear Regression: Algorithm, Use Cases, Diagnostics
  • Lab: Linear Regression

Week 4

– Advanced Analytics Theory and Methods, Part 2
  • Logistic Regression: Algorithm, Use Case, Diagnostics
  • Lab: Logistic Regression
  • Text Analytics - Methods and Metrics
  • Naïve Bayes: Algorithm, Use Cases and Diagnostics
  • Lab: Text Analytics and Naïve Bayes Classifier

Week 5

– Advanced Analytics Theory and Methods, Part 3
  • Decision Trees: Algorithm, Use Cases, Diagnostics
  • Lab: Decision Trees
  • Time-Series Analysis: Algorithm, Use Case, Diagnostics
  • Lab: Time Series Analysis

Week 6

– Advanced Analytics Technology and Tools, Part 1
  • Intro to Advanced Analytics Technology and Tools
  • MapReduce
  • Hadoop Ecosystem
  • Lab: Hadoop, HDFS, Pig, Hive, and Spark

Week 7

– Advanced Analytics Technology and Tools, Part 2
  • In-Database Analytics: SQL Essentials
  • Lab: In-Database Analytics
  • Advanced SQL and MADlib

Week 8

– Putting It All Together
  • In-Database Analytics: SQL Essentials
  • Lab: In-Database Analytics
  • Advanced SQL and MADlib
  • Block length
  • Teaching hours
  • Refreshments No
  • Exam No

This 8-week online course provides practical foundation-level training that enables immediate and effective participation in Big Data and other analytics projects. It includes an introduction to Big Data and the Data Analytics Lifecycle to address business challenges that leverage Big Data.

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