Data Science Course Fee in Bangalore
About Data Scientist Course in Bangalore
DataMites™ Data Science course in Bangalore is the structured training that lets you gain expertise in analyzing colossal volume of raw data and extracting robust, actionable analytics from it. Data Science is most happening field in business, tagged as most promising career in 21st century. Data Science courses are designed to specifically enable aspiring candidate to achieve their career goals with Data Science foundation targeted at beginners and professionals wanted to gain high level knowledge, Data Scientist course targeted at candidates aspiring to gain full knowledge on all aspects of Data Science including Programing, Statistics, Machine learning as well as business side of Data science, gaining full spectrum of data science skills to deliver end to end Data Science solutions.
It is a complete course with a detailed learning that covers a 9 course bundle of
- 1) Python for Data Science
- 2) Statistics for Data Science
- 3) Machine Learning Associate
- 4) Machine Learning expert
- 5) Time series foundation
- 6) Model deployment (Flask-API)
- 7) Deep Learning -CNN Foundation
- 8) Tableau Foundation
- 9) Data Science business concepts that helps the aspirants in specialising the area
Certified Data Scientist course that is being conducted in Bangalore comes with 2months/64 hours course duration.
The structured three phase modules of this course are
Phase 1 (15 Days)Pre-course study helps you to develop your knowledge on the basics of Data Science and Machine Learning. It is a self-study phase that needs to be completed before entering to phase 2 module. Phase 1 includes high-quality videos, E-books covering the syllabus of Basic Python Language, Basic Mathematics for Data Science, Statistics essentials for Data Science, Beginners guide to Machine Learning (E-book) and Practice Materials. Furthermore, it facilitates the candidates to practice scripts at a cloud lab conveniently.
Phase 2 (2 Months)This is the most crucial part of the training that comes with fulltime intensive training sessions through any of the convenient channels, Traditional Classroom Training, Live Instructor-Led Online Training, and Self Paced Learning / E-learning. This phase covers the next higher level syllabus of Python/R Programming, Statistics, Machine Learning Associate and expert.
Phase 3 PAT Services (4 Months)This is a dedicated part for candidates to make them market ready after the series of intensive coaching and learning. It covers 4-month Project Mentoring, exposure to 5+ detailed Industry related projects, revision sessions, access to an extensive collection of interview questions, resume support, mock interview sessions, job updates and experience certificate.
On completion of these structured three phase DataMites™ Data Science training, you are assured of gaining the essential skills and confidence to perform your "Super Hero duty" as Data Scientist.
The Key Features of Data Scientist Training in Bangalore
Project Mentoring: You can gain experience by working on live projects from global AI and ML Solution providers.
Revision Sessions: Lots of revisions and multiple opportunities to clarify your doubts with our chief Data Scientist even after course completion.
Resume Support: You can curate a customized resume at the hands of experts to make your first impression the best one.
Interview Questions: Equip yourself with the latest interview questions and answers to face the interviews confidently.
Mock Interviews: Our experts will help you to increase your job interview success rate and get hired quickly by practicing numerous mock interview sessions.
Job Updates: All latest job updates which are validated and perspective are posted regularly by PAT Team in PAT Facebook group.
DataMites™ has Asia headquarters in Bangalore, Silicon Valley of Asia, providing several courses in both classroom and online learning modes. There are atleast two batches of Certified Data Scientist course starting every month in Bangalore location with max of 30 candidates intake. Other courses including deep learning, Tableau, python/R developers, Machine Learning expert also delivered in classroom as well as online mode in Bangalore DataMites™ office near Kudlu gate.
DATA SCIENCE TRAINING COURSES IN Bangalore
Data Science Foundation is a high level Data Science course designed with agenda covering all aspects of data science with core concepts. Data Science has three board domains viz., Statistics, Machine Learning/ Programming/ Data Skills, Business Domain Knowledge.
Python is the most popular programming language for Data Science as on Today. Python is powerful , easy to learn and flexible tool for coding Data Science and Machine Learning algorithms.
DataMites Certified Data scientist with R program covers all the data analytics techniques using the latest tools like R, Python, Tableau, Machine Learning and MiniTab.
DataMites's "Business Statistics" course ensures that you learn the practical implications of this statistical tool and excel in all of its concepts. This course does include case studies for a detailed understanding and real time experience.
Data Science Course Syllabus & Schedules in Bangalore
DataMites™ Certified Data scientist is designed to provide a right blend of all four facets of Data Science
- This four facets forms four pillars for data science field. They are 1. Programing 2. Statistics 3. Machine Learning 4. Business Knowledge.
- The course is mainly focussed on Python for core data science programing, it also includes R as necessary to enable professionals working in R.
- Statistics are covered as required for a Data Scientist, you may find detailed syllabus in syllabus tab.
- Machine Learning is the main tool kit for Data Science in predicting classification or regression.
- This course courses all popular ML algorithms as detailed in syllabus tab.
- This course allows candidates to obtain an in-depth knowledge by laying a strong foundation and covering all the latest data science topics.
- The increasing demand curve for data science professionals to manage the large set of data in various organizations providing millions of job opportunities in global markets.
- The knowledge gained through this course along with IABACâ„¢ certificate surely help you to become data science professional.
This course comes as a perfect package of required Data Science skills including programing, statistics and Machine Learning. If you aspire to be Data Science professionals, this course can immensely help you to reach your goal.
After successful completion of this â€œCertified Data scientistâ€ course, you should have
- Gained a better knowledge on entire Data Science project work flow.
- Understand key concepts of statictics
- Gained hands on knowledge of popular Machine learning algorithms
- In depth knowledge on Data Mining, Data forecasting, and Data Visualization.
- Able to create business case for Data Science project
- Deliver end to end data science project to customer
Data science is the hottest field in the market as on today. Be it a small company or an MNC, they need a Data scientist to manage their large pool of data.
- High demand for data scientists with only a few qualified people to hire
- High salaries, nearly twice of an average software engineer as per Glassdoor report
- This course not only designed to enable you for new career opportunities but also allows you to apply the new age skills in your current work and become valuable to in your current role.
- Be assured that you are entering the future of data science much earlier to grab those wonderful opportunities arising from this biggest need of the business world.
This Data Science course is not restricted to any specific domain.
- Fresh Graduates or students from any discipline can choose this course to obtain better job opportunities in this most demanding data science field
- Working professionals looking to change their domain to data science field.
- Highly recommended for those who are aspiring jobs that mainly revolves around data analytics and machine learning
- Project managers aspiring to switch to manage Data Science projects
DataMites™ is the global institute for Data Science accredited by International Association of Business Analytics Certifications (IABAC). DataMites provides flexible learning options from Classroom training, Live Online to high quality recorded sessions
The 6 Key reasons to choose DataMites™
- Globally reputed certification
- Syllabus Aligned with IABAC global market standards
Elite Faculty & Mentors
- Best in industry faculty from IIMs
- Course structured by Professors in Data Science from top universities
- Ensures high quality learning experience
- Learning through case study approach
- Theory â†’ Hands On â†’ Case Study â†’ Project â†’ Model Deployment
10+ Industry Projects
- 10+ Industry related projects
- Enabling candidates to gain real time skills, also boosting confidence for real challenges
PAT (Placement Assistance Team)
- Dedicated PAT (Placement assistanceTeam)
- Resume assist service
- Mapping candidates to verified jobs by PAT team
- Supporting in Interview preparation
24x7 Cloud Lab for ONE year
- High capacity data science cloud lab
- All Machine Learning python and R scripts on cloud lab for quick reference
- Enable participants to practice Data Science even with their mobile phones through cloud lab
Data Science jobs are at highest volume in Bangalore in the year 2019. On an average about 2000 jobs are active on daily basis in portals such as LinkedIn. With largest pool of data science professionals, Bangalore is the best place for global organisations to build their data science centre of excellence.
Bangalore is the destination in India for Data Science aspirants from freshers to seasoned professionals as it has perfect ecosystem for learning and pursuing career in Data Science.
Bangalore is known as Silicon Valley of Asia and hub for IT solutions across the globe. Now, Bangalore is shaping up as hub for Data Science with highest opportunities in the field of Data Science with large pool of resources.
Even though Bangalore is quoted for largest pool of resources, it is still falling short grossly to meet the growing demand in Data Science. In the year 2018, about 80,000 jobs opportunities remain unfilled due to lack of qualified resources. This calls for more resources from beginners to experienced professionals to skill themselves in the field of Data Science.
Can I pay Data Science course fees in instalment?
Yes. DataMites has 6-month no-cost EMI option. You can avail it directly while paying on the DataMites website at checkout.
Do I have to buy any software for Data Science course?
No, most of software are free and open source. The guidelines to setup software is a part of course.
Is this Classroom or Online Data Science Course?
Certified Data Scientist is delivered in both Classroom and Online mode. Classroom is provided in selected location such as Singapore – Singapore, Bangalore-India, Hyderabad - India, Amsterdam – Netherlands, Houston – USA. Please check with the co-ordinators about training options in your location.
Is the Exam fee included in the course fee?
IABAC™ Exam fee is usually bundled as a part of total course fee. Please check with the co-ordinators for confirming the same.
What if I miss a session?
All the online sessions are recorded and shared so you can revise the missed session. For Classroom, speak to the coordinator to join the session in another batch.
Do I get Job assistance for Data Science career?
We have a dedicated PAT (Placement Assistance team) to provide 100% support in your data science career pursuit. Check out PAT services
Data Science Course Curriculum:
This course covers following concepts.
The following topics are covered here
Module 1 - Introduction to Data Science with Python
- Installing Python
- Programming basics
- Native Data types
Module 2 - Python Basics: Basic Syntax, Data Structures
- Data objects
- Comparison Operators
- Condition Statements
Module 3 - Numpy Package
- Numpy overview
- Selecting Data
- Splitting Arrays
Module 4 - Pandas Package
- Pandas overview
- Series and DataFrame
Module 5 - Python Advanced: Data Mugging with Pandas
- Treating Missing Values
- Removing Duplicates
- Transforming data
Module 6 - Python Advanced: Visualization with MatPlotLib
- Importing MatPlotLib & Seaborn Libraries
- Creating basic chart : Line Chart, Bar Charts and Pie Charts
- Ploting from Pandas object
- Saving a plot
- Object Oriented Plotting : Setting axes limits and ticks
- Multiple Plots
- Plot Formatting : Custom Lines, Markers, Labels, Annotations, Colors
- Satistical Plots with Seaborn
Module 7 - Exploratory Data Analysis:
- Data Cleaning
- Data Wrangling
Module 8 - Exploratory Data Analysis: Case Study
The following topics are covered here
Module 1: Introduction to Statistics
- Descriptive and Inferential Statistics
- Types of Data
Module 2: Harnessing Data
- Types of Sampling Data
- Simple Random Sampling
- Cluster Sampling
- Sampling Error
Module 3: Exploratory Analysis
- Median and Mode
- Data Variability
- Standard Deviation
Module 4: Distributions
- Normal Distribution
- Central Limit Theorem
- Histogram - Normalization
- Normality Tests
Module 5: Hypothesis & computational Techniques
- Hypothesis Testing
- Null Hypothesis
- Type I & II errors
- Parametric Testing: T - Tests
- Anova Test
- Non-Parametric Testing
- Ascerting accuracy of Data
Module 6: Correlation & Regression
- Introduction to Regression
- Type of Regression
- Hands on of Regression with R and Python.
- Weak and Strong Correlation
- Finding Correlation with R and Python
The following topics are covered here
Module 1: Machine Learning Introduction
- What is Machine Learning
- Machine Learning vs Artificial Intelligence
- Machine Learning Workflow
- Statistical Modeling of Machine Learning
- Application of Machine Learning
Module 2: Machine Learning Algorithms
- Popular Machine Learning Algorithms
- Clustering, Classification and Regression
- Supervised vs Unsupervised Learning
- Choice of Machine Learning
Module 3: Supervised Learning
- Simple and Multiple Linear Regression
- KNN etc...
Module 4: Linear Regression and Logistic Regression
- Theory of Linear Regression
- Hands on with use Cases
Module 5: K-Nearest Neighbour (KNN)
Module 6: Decision Tree
Module 7: NaÃ¯ve Bayes Classifier
Module 8: Unsupervised Learning
- K-means Clustering
The following topics are covered here
Module 1: Advanced Machine Learning Concepts
- Tuning with Hyper Parameters
- Popular ML Algorithms
- Clustering, Classification and Regression
- Supervised vs Unsupervised
- Choice of ML Algorithm
Module 2: Random Forest â€“ Ensemble
- Ensemble Theory
- Random Forest Tuning
Module 3: Support Vector Machine (SVM)
- Simple and Multiple Linear regression
Module 4: Natural Language Processing (NLP)
- Text Processing with Vectorization
- Sentiment analysis with TextBlob
- Twitter sentiment analysis.
Module 5: NaÃ¯ve Bayes Classifier
- NaÃ¯ve Bayes for text classification
- New Articles Tagging
Module 6: Artificial Neural Network (ANN)
- Basic ANN network for regression and classification
Module 8: Tensorflow overview and Deep Learning Intro
- Tensorflow work flow demo and intro to deep learning
Module 1: What is Time Series?
Module 2: Trend, Seasonality, cyclical and random
Module 3: White Noise
Module 4: Auto Regressive Model (AR)
Module 5: Moving Average Model (MA)
Module 6: ARMA Model
Module 7: Stationarity of Time Series
Module 8: ARIMA Model â€“ Prediction Concepts
Module 9: ARIMA Model Hands on with Python
Module 10: Case Study Assignment on ARIMA
Module 1: REST API
- API Concepts
- Web Servers.
- URL parameters
Module 2: FLASK Web framework
- Installing Flask
Module 3: API in Flask
- API Coding in Flask
Module 4: End to End Deployment
- Exporting trained model
- Creating End to End API
Module 1: Image Processing fundamentals
- Image Basics
- Converting Image to Numpy Array
Module 2: Introduction to CNN
- Convolution â€“ Feature Maps
- Max Pooling
Module 3: Image Classification (Cats and Dogs)
- Keras with Tensorflow
- Hands on Image Classification CNN
Module 1: Understanding Business Case
- Components of Business Case
- ROI Calculation Techniques
Module 2: Writing Data Science Business Case
- Defining Business Opportunity
- Translating to Data Science problem
- Creating project plan
Module 3: Benefits Analysis
- Demonstrating Break Even and Benefits Analysis with Data Science Solutions
Module 4: Starting project, Setting up Team and closing
- Initiating Project
- Setting up the Team
- Delivering and Closing Project
Module 1: Tableau Introduction
- Tableau Interface
- Dimensions and Measures
- Filter Shelf
- Distributing and Publishing
Module 2: Connecting to Data Source
- Connecting to Sources
- Data Bases
- Extracting and interpreting data
Module 3: Visual Analytics
- Charts and Plots with Super Store Data
Module 4: Forecasting
- Forecasting Time Series Data