- Data Science Terminologies
- Evolution Of Data Science
- What Is Data Science?
Beginner
Online
3 Months
₹ 22,448 45,000
Quick facts
particular | details | |
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
+1 more
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Mode of Delivery
Video and Text Based
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Course overview
The Data Science Associate course is developed for those looking to enter the promising fields of data science, machine learning, or artificial intelligence. It explores essential topics like predictive modelling, machine learning, and programming languages like Python and R.
The Data Science Associate course syllabus includes topics like SQL, Machine Learning, Statistics, Big Data, Deep Learning, Neural Networks, Python, R. It also explores the evolution of data science and how it is different from business analytics and big data.
Moreover, the training programme features some highly valuable case studies and real-world projects. Upon completing the Data Science Associate online training, you also receive an IABAC certification. Since this document is globally recognised, attaching it to your CV/Resume will open a ton of opportunities for you worldwide.
You also get to choose between three learning approaches – live virtual, blended learning, and classroom -, thereby allowing you to navigate the course per your preferred learning style.
The highlights
- 10 Capstone projects
- 1 client project
- Internship + Job assistance
- IABAC Global certification
- Blended learning
- Classroom learning
- Instructor-led live coaching
- Specialised syllabus
Program offerings
- Iabac global certification
- Specialised curriculum
- Blended learning
- Classroom learning
- Capstone projects
- Client projects
- Internship + job assistance
Course and certificate fees
Fees information
To get access to the Data Science Associate online training, you must pay the programme fee. You can choose from the three enrolment options provided by DataMites - blended, live virtual, and classroom. Here are the pricing details for each option.
Data Science Associate fee structure
Mode of learning | Total Fee | Discounted Fee |
Live Virtual | Rs. 45,000 | Rs. 21,353 |
Blended Learning | Rs. 27,000 | Rs. 11,603 |
Classroom | Rs. 45,000 | Rs. 28,178 |
certificate availability
certificate providing authority
Eligibility criteria
To get the most out of the Data Science Associate online course, you must have basic knowledge of machine learning, statistics, and mathematics. Moreover, you must also possess a curious mind and problem-solving skills.
The certificate of completion is awarded after you have completed the course, projects, and cleared the final exam.
What you will learn
Upon completing the Data Science Associate syllabus, you will have a firm grasp of computer vision and its various real-life applications. Moreover, you will also gain proficiency over concepts like:
- Statistics
- Deep Learning
- Neural Networks
- Python
- R
- SQL
- Machine Learning
- Big Data
- AI
Who it is for
The Data Science Associate online training is ideal for:
- Machine learning and Data science enthusiasts
- Graduate Freshers
- Business Analysts
- Experienced Data Scientists
Admission details
- To enrol in DataMites’ Data Science Associate online training, you first need to visit the programme page.
- Go through the programme details carefully. Once you’ve done that, you can proceed by clicking the ‘Enquire Now’ option on the top of the page.
- A small enquiry form will pop up. Enter your email address, name, company name, and phone number. After submitting the information, DataMites will get in touch with you promptly.
The syllabus
Introduction to Data Science
Data Science Vs. Business Analytics Vs. Big Data
Comparing Various Related Domains With Data Science
Classification Of Business Analytics
- Discovery Analytics And Prescriptive Analytics
- Predictive Analytics
- Descriptive Analytics
Data Science Project Workflow
- Data Science Project Workflow
- Crips – Dm Framework
Roles In Data Science
- Industry Roles And Responsibilities
Application Of Data Science In Various Industries
- Finance & Banking
- Health Care
- Manufacturing
- Human Resource
- Retail
- Logistics
Python Installation And Setup
- Terms
- Definitions
- Types Of Data
- Descriptive And Inferential Statistics
Harnessing Data
- Simple Random Sampling
- Types Of Sampling Data
- Stratified
- Sampling Error
- Cluster Sampling
Exploratory Analysis
- Mean
- Data Variability
- Median And Mode
- Standard Deviation
- Outliers
- Z-Score
Distributions
- Central Limit Theorem
- Normal Distribution
- Normalisation
- Histogram
- Skewness
- Kurtosis
- Normality Tests
R Introduction
- R Studio – R Development Environment
- R Installation And Setup
- R Language Basics
R Data Science
- R Data Science Packages Exploration
- R Control Statements
- Project In R
- R Data Structures
Introduction To Statistics
- Terms
- Types Of Data
- Descriptive And Inferential Statistics: Definitions
Correlation & Regression
- Correlation With Strong And Weak Correlation
- Direct And Indirect Correlation
- Calculating Correlation With Python
- Simple Linear Regression With Python
- Regression Theory
Numpy Numerical Python Package
- Numpy Basics
- Introduction
- Structure And Content Of Arrays
- Creating Numpy Arrays
- Subset
- Index And Iterate Through Arrays
- Slice
- Python Lists Vs. Numpy Arrays
- Multidimensional Arrays
Operations On Numpy Arrays
- Basic Linear Algebra Operations
- Operations On Arrays
- Basic Operations
Pandas Panel Data Package
- Indexing And Selecting Data
- Pandas Basics
- Merge And Append
- Lambda Function & Pivot Tables
- Grouping And Summarizing Dataframe
Data Cleaning Data Munging With Pandas
- Indexing And Selecting Data
- Pandas Basics
- Merge And Append
- Lambda Function & Pivot Tables
- Grouping And Summarizing Dataframe
Basics Of Visualisation
- Data Visualization Toolkit
- Components Of A Plot
- Sub-Plots
- Functionalities Of Plots
Plotting Categorical And Time Series Data
- Plotting Aggregate Values Across Categories
- Introduction
- Bivariate Distributions - Plotting Pairwise Relationships
- Plotting Distributions Across Categories
- Vectors: The Basics
- Vector Spaces
Plotting Data Distributions
- Univariate Distributions
- Univariate Distributions - Rug Plots
- Introduction
Machine Learning Introduction
- ML Workflow
- What is ML? ML Vs. AI
- Application Of ML
- Statistical Modeling Of ML
Machine Learning Algorithms
- Clustering
- Popular Ml Algorithms
- Classification And Regression
- Choice Of Ml Algorithms
- Supervised Vs. Unsupervised
Simple Linear Regression
- Best Fit Line
- Regression Line
Linear Regression In Python
- Reading And Understanding The Data
- Assumptions Of Simple Linear Regression
- Building A Linear Model
- Hypothesis Testing In Linear Regression
- Linear Regression Using Sklearn
- Residual Analysis And Predictions
Multiple Linear Regression
- Multicollinearity
- Simple Linear Reg Vs. Multiple Linear Reg
- Dealing With Categorical Variables
- Feature Selection
- Model Assessment And Comparison
Logistic Regression Binary Classifier
- Binary Classification
- Introduction: Univariate Logistic Regression
- Finding The Best Fit Sigmoid Curve Summary
- Sigmoid Curve
Logistic Regression Model Building
- Data Cleaning And Preparation
- Multivariate Logistic Regression
- Feature Elimination Using RFE
- Building Your First Model
- Manual Feature Elimination
- Confusion Matrix And Accuracy
Install SQL Packages And Connecting To DB
- PymySQL
- SQLalchemy
RDBMS (Relational Database Management) Basics
- Foreign Key
- Basics Of SQL DB
- Primary Key
Select SQL Command, Where Condition
- Where Condition To Pandas Data Frame
- Retrieving Data With Select SQL Command
Advanced SQL
- Group By Clause
- Nested Queries
- Having Clause
- Inner Join, Outer Joins, Multi Join
- Aggregate Functions
- Order By Clause
Data Science: Project Structure
- 6-Phase Project Execution
- Crisp Dm Framework
Business Aspects
- Challenges And Pitfalls
- Project Management Methodology
- Ml Use Case Development
Evaluation process
You are automatically registered for the Data Science Associate classes certification exam when you enrol in the course. The examination fee is included in the programme fee. You can appear for the exam as and when you see fit.
How it helps
When you enrol for the Data Science Associate live training, you get not only a career-focused curriculum but also a dedicated team beside you to help you every step of the way. With this course, you get the opportunity to work on various data science projects that will help you ramp up your skills in no time. If you’re a working professional, you can apply your skills to make insightful decisions in your day-to-day tasks, thereby reducing costs and maximising profits in the process.
You can also land lucrative job roles by embellishing your CV/Resume with the course completion certificate.
FAQs
No coding experience is required to enrol in this programme.
No, DataMites only accepts full upfront payment.
No, you must pay any exam fee since it is included with the course fee.
The certification is offered by IABAC: International Association of Business Analytics Certification.
This course is taught by subject matter experts in data science, AI, and machine learning.
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