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Data Science Course
To become adept in the fundamental concepts and practices of Python. Master the use of Python for advanced Data Science and Machine Learning.
Online
₹ 25,000
Quick facts
particular | details | ||
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekends
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Course overview
The Data Science programme by Digital Vidya has been created and curated by industry experts having years of experience. The curriculum has been vetted by over 2800 enterprises to be made industry-compliant. Besides, the Data Science training course will help you take that crucial step in becoming a Data Scientist.
You will receive instructions about variables, data types, and all the various operators—logical, arithmetic, and comparison—to come to terms with the language of Python. Additionally, you will also learn about Data Manipulation techniques using the Pandas library, along with the required skills for Regression Analysis, Decision Trees and Forests, and Statistics.
You will be required to solve the Capstone Projects in the Digital Vidya Data Science course. As a result, you will increase your industry knowledge in the niches of Natural Language, Deep Learning, Bank Management, and Healthcare Analysis.
Furthermore, you will be eligible to receive two certifications—one from Digital Vidya, and the other from NASSCOM. The former will be available after you complete all of the assignments and at least one Capstone Project. Upon completing the Data Science Programme successfully, you will get the NASSCOM FutureSkills Certification as well.
The highlights
- Live question and answer sessions
- Lifetime access to the study material
- Study at your convenience
- Training by industry experts
- 72+ hours’ worth practical assignments
- 100+ training and exercise modules
- Resume building assistance
- Dedicated placement cell
- NASSCOM curriculum and certificate of completion
- Guaranteed interviews after course completion
- Student discount of 15%
Program offerings
- Training from industry experts
- Live q and a sessions
- Practical projects
- Remote and convenient learning
- Lifetime access to revised content
- Training by industry experts
- Dedicated placement cell
- Nasscom certification
Course and certificate fees
Fees information
The Data Science certification course fee is made up of the course fee and the applicable GST. Candidates can also avail a 15% discount on the Data Science course fee.
Data Science Certification Course Fee Structure
Training Option | Fee in INR |
Online training course | Rs. 25,000 + GST |
certificate availability
certificate providing authority
Eligibility criteria
You need not be a programmer to undertake this Data Science Certificate Course. Non-programmers with good analytical skills and a zeal to learn about data science will find the Digital Vidya Data Science Course to be equally rewarding.
Certificate Qualifying Details
You will receive the “Data Scientist” certification from Digital Vidya after they solve a solitary Capstone Project. Industry experts will award you the certificate after assessing your projects and assignments.
What you will learn
Digital Vidya is offering a comprehensive Data Science Course syllabus outlining the crucial aspects of “end-to-end data science”. The Data Science programme will help strengthen your basics; including Machine Learning, Exploratory Data Science, SQL, and statistics. Additionally, after Data Science certificate course completion, you should be able to perform the following:
Who it is for
The Data Science Specialisation course is tailor-made to ensure that individuals with a grasp of programming knowledge can upskill and become Data Scientists. The Students of B.Tech/ BE/MCA /MCS who wish to enter the field of Artificial Intelligence, Machine Learning, or Data Analytics can also take Data Science classes.
Admission details
Follow these steps to apply for the Data Science Course by Digital Vidya:
Step 1. Access the course on the official Digital Vidya website by visiting https://www.digitalvidya.com/data-science-course/
Step 2. Click on the “Enroll Now” button.
Step 3. Enter your necessary details. You may proceed to pay the fees through your preferred mode. Do remember to download the fee receipt for future reference.
Filling the form
You can register for the Data Science programme by filling an application form. In the application form, enter your name, email id, and phone number for applying to the Data Science online course. You can also select whether to take a free orientation session or not; also, if you wish to receive the Data Science curriculum via email.
The syllabus
Data Science and Analytics
Fundamentals of Python
- Installation
- Syntax
- Datatypes and Variables
- Lists
- Date & Time
- Reading a File
- Writing into File
- If. Else. Statements
- Numbers
- Sequences
- Sets
- Operators Dictionary
- Strings
- Tuples
- For Loop
- While Loop
- Class & Objects
- Break
- Continue
- Modules and Packages
- Pass
- Ranges Functions
- Exceptions
- Mathematics
- Regular Exp
MySQL and Python
- Setting up the Environment
- Creating Databases
- Connecting Databases
- Tables
- Inserting Operations
- Reading Operations
- Joining Operations
- Operations Update
- Transactions
Numpy
- Creating Arrays
- Basic and Advanced Indexing
- ND array
- Data Type Objects
- Numpy and Dtypes
- Linear Algebra and Slicing
- Mathematical functions
- Binary Operations
- Searching, Sorting and Counting
- Array iterations
- Strings
- Multiplying Matrices
Data Analysis and the Pandas DataFrame
Data Analysis
- Visualisation with Bokeh
- Data Analysis and Python
- Python and Visualisation in Different Charts
- Mathematics Operations
Pandas DataFrame
- Pandas Dataframe Creation
- Rows and Columns
- Indexing
- Boolean Indexing
- Conversion Functions
- Negotiating Through Missing Data
- Date and Time
- Merging, Joining, and Concatenating
Fundamentals of Statistics
- Bayes’ Theorem
- Location
- Spread
- Prior, Likelihood and Posterior
- Random Variables
- Graphical Representation of Single Variables
- Correlation and Covariance
- Continuous Random Variables
- Distribution Functions
- Bivariate Data
- Probability, Multiple Probability, and Conditional Probability
- Different Distribution Types
- Scatterplot
- Varying Estimation Types
- Independent Occurrences
- Association of Multiple Variables
- Binomial Distributions
- Exploring various Hypothesis Types
Machine Learning and Python
- Applying Machine Learning
- Types of Learning
- Suitable libraries for Machine Learning
Classification and Regression
Classification
- Understanding Classification
- Distance Theory of Euclid
- K Nearest Neighbors’ Application
- Types of trees
- Random forests
- Analysing Principal Component and Linear Discriminant
- Algorithm Boost
Regression
- Features and Labels
- Theory
- Predictions
- Testing and Training
- Best Fit Slope and Best Fit Line
- Evaluation Methods
- Coefficient of Determination and R Squared
Understanding Support Vector Machine
- Basics of Vector
- Fundamentals of Support Vector Machine (SVM)
- Constraint Optimization
- SVM Optimisation and Python
- Forecasting and Visualisation using Custom SVM
- Kernels
- Soft Margin Support
Machine Learning and Clustering
- K-means and Python
- Titanic Dataset and K-Means
- Completing K-Means
- Tackling Non-Numerical Data
- Understanding Naïve Bayes Classifier and Scikit
- Classifying Text using Naïve Bayes
- Understanding Clustering Hierarchy and Mean Shift
- Text Classification and Python
Recommender Systems
Collaborative Filtering of Content-Based Recommender Systems
Understanding NLP
- Levenshtein Distance
- Pre-processing Text
- Dependency Grammar
- Detecting Phrases
- Removing Noise
- Tagging Part of Speech
- Normalising Lexicon
- Stemming
- Topic Modelling
- and Density
- Readability
- Embedding Words
- Standardising Objects
- N-Grams
- Statistical Features
- Frequency Feature Engineering
- Classifying and Matching Texts
- Phonetic Matching
- Syntactic Parsing
- Entity Parsing
- Recognition of Named Entity
- NLP
- Flexible String Matching
- NLP Libraries
How it helps
The most significant feature of the Data Science certification course is that it is NASSCOM certified. The course has been vetted to ensure that it adheres to industry standards of what is expected of a Data Scientist.
Upon completion of the Data Science programme, you will continue to enjoy unlimited access to the learning modules, which are programmed to be updated on a real-time basis. Digital Vidya also boasts of a competent placement network which will assist you in building and distributing your resume. Furthermore, you are guaranteed a 100% interview opportunity to help you jumpstart your dream career.
Instructors
Mr Ganesh Naik
Instructor
Freelancer
Mr Pritesh Shrivastava
Data Scientist
Flipkart Pvt. Ltd.
Mr Rohit Kumar
Instructor
Freelancer
Ms Vaishali Garg
Instructor
Freelancer
Mr Nitika Malhotra
Instructor
Freelancer
Mr Rushabh Shah
UI Developer
Freelancer
Mr Dilnoor Singh
Instructor
Freelancer
Mr Shaheer Ahmad Khan
Europe Researcher
Freelancer
FAQs
Our world is making rapid advancements in the virtual space. Incidentally, the demand for talent far outweighs the supply. NASSCOM reports that there is roughly a 1,40,000 gap between demand and supply. The need of the hour is Data Science, and this Data Science training programme will provide you with the requisite knowledge to make a mark in this niche.
You can audit the Data Science training course by taking the demo session offered by Digital Vidya to decide whether you should take the online classes.
Digital Vidya is committed to providing the best learning experience for you, but the support does not end there. After Data Science online course completion, you can expect full placement support, and 100% guaranteed interview assistance.
The packages on offer differ from organization to organization. Since the Data Science certification is based on a curriculum created by NASSCOM and is also certified by it, you can expect to get an industry-standard package.
Start-ups and boutique firms offer the maximum scope for employment. They are willing to employ fresher applicants and incorporate young blood.
Yes, you can do all of the above. But remember that it could take a while before your next job offer. Moreover, you increase your options when you are willing to relocate anywhere.
There is no refund policy.