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Data Science course

Objective – Data Analytics Training Course New Delhi, Data Science Training Course New Delhi

 

The objective of Data Analytics and Data Science course is to master study of data science to become a successful data scientist. The course aims to equip the data scientist to successfully carry out data analysis to include tools for carrying out massive data management , statistical modelling and provide algorithm for data mining such as clustering and associate rule mining to name a few.

The course primarily covers the complete range of Statistical Software Course & R-Programming Course and machine language learning techniques as defined in the Data Science study.

Please Note: All below course content will be covered in practical scenarios and regular assignments will be shared. All sessions will be recorded and shared with student for future reference (free of cost). Along with below course.

 

Scope of the program

After undertaking the course, one aims to achieve the proficiency in the following:

  • Understand the basic role played by the Data scientist in analyzing the Data Analysis Life cycle.
  • Analyze Big data by the use of Statistical Software and R statistically.
  • Learn Predictive Analytics, Machine Learning & Data mining Techniques
  • Insight in to various Machine Learning Techniques and their implementation using R.
  • Handling tools and techniques involved in sampling, filtering and data transformation

Who Should Enroll

The course is a blend of two major open source tools available viz.Statistical Software and R language. The course is ideal for you if you are:

  • A Professional working on Database management and streaming of Big Data.
  • IT or Management student who are passionate about problem solving methodologies.
  • Professionals who are expert in their domain and strive to learn technology for business and technology integration.

Section : 1 Analytics with Statistical Software Programming

  1. Introduction to Analytics and Basic Statistics
  2. Hypothesis Testing
  3. T-Test
  4. ANOVA
  5. Chi-Square
  6. Linear Regression
  7. Logistic Regression
  8. Cluster Analysis
  9. Time Series

Section 3 : Analytics with Python Programming

  1. Basic Statistics
  2. Hypothesis Testing
  3. T Test, Z Test, F Test
  4. Correlation
  5. ANOVA, MANOVA, ANCOVA
  6. Linear regression
  7. Logistic regression
  8. Cluster Analysis
  9. Time Series
  10. Decision Tree
  11. Random Forest
  12. Text Analytics
  13. Sentiment Analysis
  14. Social Media Analytics

Section :2 Python Programming

  1. Introduction to Python
  2. Data Structure
  3. Getting Data from Differences Sources (Import/Export)
  4. Functions
  5. Data Transformation
  6. Data Formatting
  7. Restructuring Data
  8. Looping Structure
  9. Graphics

Section 4: Advance Excel

  1. Functions
  2. Data Analysis
  3. Pivot Tables
  4. Interactive charts
  5. What-if-analysis, GOAL SEEK
  6. Linking Multiple Sheets
  7. Sub Total Reports, Auto Filter
  8. Password Protecting Worksheets
  9. Dashboard
  10. Record a Macro/VBA
  11. Editing a VBA Code
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Students Testimonials

  • Seeing the demand of Python in programming, I decided to enroll for weekend classes of Python then after joining, Ankit sir took our class and from the beginning we attended all the classes..

    gaurav saini

  • Ankit sir is one of the best mentors I have ever had and he's supportive also . He's is the professional in every branch he know and....

    Anshul

  • Ankit sir is the best trainer and have best knowledge in coding he is the best teacher and also supports the idea help to develop them

    rishabh jain
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