DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS

DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS using R Programming, PYTHON Programming, WEKA Tool Kit and SQL

4.27 (59 reviews)
Udemy
platform
English
language
Data Science
category
DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS
500
students
72.5 hours
content
Mar 2019
last update
$44.99
regular price

What you will learn

DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS using R, PYTHON, WEKA and SQL

This course is designed for any graduates as well as Software Professionals who are willing to learn data science in simple and easy steps using R programming, Python programming, WEKA tool kit and SQL.

Why take this course?


_Course Instructor: DATAhill Solutions Srinivas Reddy
Course Title: DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS using R Programming, PYTHON Programming, WEKA Tool Kit, and SQL
_Headline: Unleash Your Data's Potential: Master Data Science, Machine Learning & Data Analytics with R, Python, WEKA, and SQL! πŸ“Šβœ¨**


Course Description:

Embark on a journey to transform raw data into meaningful insights and actionable strategies with our comprehensive "DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS" course. This program is tailored for graduates and software professionals looking to master the art of data science through simple, step-by-step learning experiences.


Why This Course? πŸš€

  • Data is the New Oil: In the digital age, understanding data is as critical as the oil was in the industrial era. Mastering data science opens doors to a plethora of opportunities across various industries.
  • Versatile Programming Languages: R and Python are at the forefront of data science. With their extensive libraries and features, they're your go-to tools for tackling complex data challenges.
  • Hands-On with WEKA: The WEKA toolkit is an indispensable resource for machine learning and data mining tasks. Learn to harness its power effectively.
  • SQL Skills: Get proficient in SQL, the universal language for querying relational databases that underpin most data science projects.

Course Highlights:

  • Complete Data Science Cycle: From data collection and cleansing to prediction model deployment, gain a deep understanding of the entire lifecycle.
  • R & Python Mastery: Dive into advanced techniques in statistical analysis, regression modeling, hypothesis testing, and more with R and Python.
  • Machine Learning & Deep Learning: Explore the realms of machine learning, deep learning, neural networks, predictive analytics, and natural language processing.
  • Data Visualization: Learn to visualize data effectively with tools that make complex datasets understandable at a glance.
  • Practical Applications: Engage in hands-on projects that cover text mining, predictive modeling, and deployment of solutions.
  • R Studio & Libraries: Get comfortable with the RStudio interface and essential libraries for data science.
  • Comprehensive Skill Set: This course is designed to equip you with a wide array of skills, from data exploration to model interpretation.

What You'll Learn:

  • Data Collection & Extraction: Techniques for gathering and extracting data efficiently.
  • Data Cleaning & Preprocessing: Methods for cleaning datasets and preparing them for analysis.
  • Exploratory Data Analysis (EDA): Learn to explore your data and draw initial insights from it.
  • Data Transformation & Feature Engineering: Master the art of transforming data and engineering features that improve model performance.
  • Data Integration & Mining: Combine disparate datasets and uncover hidden patterns and correlations.
  • Predictive Modeling: Build accurate predictive models using various algorithms and techniques.
  • Machine Learning Algorithms: Understand and apply different machine learning algorithms, including decision trees, random forests, support vector machines, and neural networks.
  • Deep Learning & Neural Networks: Gain insights into the complexities of deep learning for tackling unstructured data.
  • Natural Language Processing (NLP): Learn to process and analyze large volumes of text data using NLP techniques.
  • Deployment of Models: Learn to take your models out of the lab and deploy them in real-world applications.

Who Should Take This Course? πŸ‘₯

This course is ideal for:

  • Graduates seeking to transition into the data science field.
  • Software Professionals looking to enhance their current skill set with data science expertise.
  • Anyone interested in understanding the practical applications of R, Python, WEKA, and SQL in the context of data science, machine learning, and data analytics.

Your Path Forward:

Join us on this enlightening journey where you'll transform into a Data Science professional ready to tackle the world's most challenging data problems. Enroll now and take your first step towards becoming a data guru! πŸŒŸπŸ“š

Screenshots

DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS - Screenshot_01DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS - Screenshot_02DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS - Screenshot_03DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS - Screenshot_04

Related Topics

2247954
udemy ID
01/03/2019
course created date
23/11/2019
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