DATA SCIENCE ASSOCIATE

This course is designed to impart practical knowledge of essential data science concepts. The syllabus includes Python essentials, data preparation with Python, statistics, descriptive analytics, business intelligence basics, Machine Learning essentials, and predictive analytics

DATA SCIENCE ASSOCIATE Training Cost

Live Virtual

740
289

  • IBM® & IABAC® Certification
  • 3-Month Course
  • 10 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Self Learning

440
159

  • IBM® & IABAC® Certification
  • 365 Days Flexi Pass + Cloud Lab
  • 10 Capstone & 1 Client Project
  • Internship + Job Assistance

Classroom

 

  • IBM® & IABAC® Certification
  • 3-Month Course
  • 10 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

Why Datamites

Why DataMites Infographic

Description

The Certified Data Science Associate course helps in gaining an understanding of Computer Vision and it’s applications in a real-world scenario. Other knowledge areas include:

  • Machine Learning
  • Neural Networks 
  • Deep Learning
  • Python and R.
  • Problem-solving skills
  • Curious mind
  • Basic knowledge of Statistics and Mathematics.
  • Knowledge of Machine Learning.  
  • Graduate Freshers
  • Data Science and Machine Learning enthusiasts
  • Experienced Data Scientists.
  • Business Analysts
  • Gain knowledge of employing data science in the day to day activities.
  • Better decision making.
  • Cost reduction.
  • Maximise profits.
  • An authorized institute by the International Association of Business Analytics Certifications (IABAC™) providing global data science certification courses
  • Founded by Data Science/Analytics Experts, who have deep roots in providing management consulting to major companies in India, Europe and USA.
  • Delivered 20+ sessions for Senior Executives of tier-1 companies in India including, CTS, TVS Group, Rane Group etc.,
  • In collaboration with CII - Confederation of Indian Industry, conducted workshops for Senior executives in India.
  • DataMites has in-house faculties who are from elite universities, IIM’s and PH.Ds in Data Science.

Syllabus

  • What Is Data Science?
  • Evolution Of Data Science
  • Data Science Terminologies
  • Comparing Various Related Domains With Data Science
  • Descriptive Analytics
  • Predictive Analytics
  • Discovery Analytics And Prescriptive Analytics
  • Crips – Dm Framework
  • Data Science Project Workflow
  • Industry Roles And Responsibilities
  • Health Care
  • Finance & Banking
  • Manufacturing
  • Retail
  •  Logistics
  • Human Resource
  • Descriptive And Inferential Statistics
  • Definitions
  • Terms
  • Types Of Data
  • Types Of Sampling Data
  • Simple Random Sampling
  • Stratified
  • Cluster Sampling
  • Sampling Error
  • Mean
  • Median And Mode
  • Data Variability
  • Standard Deviation
  • Z-Score
  • Outliers
  • Normal Distribution
  • Central Limit Theorem
  • Histogram
  • Normalization
  • Normality Tests
  • Skewness
  • Kurtosis
  • R Installation And Setup
  • R Studio – R Development Environment
  • R Language Basics
  • R Data Structures
  • R Control Statements
  • R Data Science Packages Exploration
  • Project In R
  • Descriptive  And Inferential Statistics. Definitions
  • Terms
  • Types Of Data
  • Types Of Sampling Data. Simple Random Sampling
  • Stratified
  • Mean
  • Median And Mode
  • Data Variability
  • Standard Deviation
  • Z-Score
  • Outliers
  • Normal Distribution
  • Central Limit Theorem
  • Histogram
  • Normalization
  • Normality Tests
  • Skewness
  • Kurtosis
  • Direct And Indirect Correlation
  • Correlation With Strong And Weak Colleration
  • Calculating Correlation With Python
  • Regression Theory
  • Simple Linear Regression With Python
  • Introduction
  • Numpy Basics
  • Creating Numpy Arrays
  • Structure And Content Of Arrays
  • Subset
  • Slice
  • Index And Iterate Through Arrays
  • Multidimensional Arrays
  • Python Lists Vs Numpy Arrays
  • Basic Operations
  • Operations On Arrays
  • Basic Linear Algebra Operations
  • Pandas Basics
  • Indexing And Selecting Data
  • Merge And Append
  • Grouping And Summarizing Dataframe
  • Lambda Function & Pivot Tables
  • Pandas Basics
  • Indexing And Selecting Data
  • Merge And Append
  • Grouping And Summarizing Dataframe
  • Lambda Function & Pivot Tables
  • Components Of A Plot
  • Data Visualization Toolkit
  • Functionalities Of Plots
  • Sub-Plots
  • Introduction
  • Plotting Aggregate Values Across Categories
  • Plotting Distributions Across Categories
  • Bivariate Distributions - Plotting Pairwise Relationships
  • Vector Spaces
  • Vectors: The Basics
  • Introduction
  • Univariate Distributions
  • Univariate Distributions - Rug Plots
  • What is Ml? Ml Vs AI
  • Ml Workflow
  • Statistical Modeling Of Ml
  • Application Of Ml
  • Popular Ml Algorithms
  • Clustering
  • Classification And Regression
  • Supervised Vs Unsupervised
  • Choice Of Ml Algorithms
  • Regression Line
  • Best Fit Line
  • Assumptions Of Simple Linear Regression
  • Reading And Understanding The Data
  • Hypothesis Testing In Linear Regression
  • Building A Linear Model
  • Residual Analysis And Predictions
  • Linear Regression Using Sklearn
  • Simple Linear Reg Vs Multiple Linear Reg
  • Multicollinearity
  • Dealing With Categorical Variables
  • Model Assessment And Comparison
  • Feature Selection
  • Introduction: Univariate Logistic Regression
  • Binary Classification
  • Sigmoid Curve
  • Finding The Best Fit Sigmoid Curve Summary
  • Multivariate Logistic Regression
  • Data Cleaning And Preparation
  • Building Your First Model
  • Feature Elimination Using Rfe
  • Confusion Matrix And Accuracy
  • Manual Feature Elimination
  • Basics Of Sql Db
  • Primary Key
  • Foreign Key
  • Retrieving Data With Select Sql Command
  • Where Condition To Pandas Data Frame.
  • Order By Clause
  • Aggregate Functions
  • Group By Clause
  • Having Clause
  • Nested Queries
  • Inner Join, Outer Joins, Multi Join
  • Crisp Dm Framework
  • 6-Phase Project Execution
  • Ml Use Case Development
  • Project Management Methodology
  • Challenges And Pitfalls

FAQ'S

The trainers for the Certified Data Science Associate  course have experienced Data Scientists, AI and Machine Learning experts who possess good knowledge of the subject matter.

 No. Coding is not required to learn Certified Data Science Associate courses.

You can enrol for the Certified Data Science Associate Course by visiting our website, and doing the payment through Debit/Credit card, Visa. The receipt for the payment done will be sent to your registered E-mail id.

Yes. You will be given a certificate after the completion of the Certified Data Science Associate course.

You will receive certification from IABAC® - International Association of Business Analytics Certification.

This course is perfectly aligned to the current industry requirements and gives exposure to all the latest techniques and tools. The course curriculum is designed by specialists in this field and monitored and improved by industry practitioners on a continual basis.

No, the exam fees are already included in the course fee and you will not be charged extra.

Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constraints, your relation manager at DataMites™ shall assist you with part payment agreements

DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on an individual basis in assisting for the right Data Science job.

Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constraints, your relation manager at DataMites™ shall assist you with part payment agreements

You get a 100% refund training fee if the training is not to your satisfaction but the exam fee will not be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis

DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with the latest information on Data Science as well as job updates.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • Job connect
  • Resume Building
  • Mock interview with industry experts
  • Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

Data Science Interview Questions

Data Science Projects

Trending Courses in INDIA

REVIEWS

HELPFUL RESOURCES - DataMites Official Blog




RECOMMENDED COURSES