DATA SCIENCE CERTIFICATION AUTHORITIES

Data Science Course Features

DATA SCIENCE LEAD MENTORS

DATA SCIENCE COURSE FEE IN SANGLI, INDIA

Live Virtual

Instructor Led Live Online

110,000
59,451

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Live Online Training
  • 25 Capstone & 1 Client Project
  • 365 Days Flexi Pass + Cloud Lab
  • Internship + Job Assistance

Blended Learning

Self Learning + Live Mentoring

66,000
34,951

  • Self Learning + Live Mentoring
  • IABAC® & NASSCOM® Certification
  • 1 Year Access To Elearning
  • 25 Capstone & 1 Client Project
  • Job Assistance
  • 24*7 Leaner assistance and support

Classroom

In - Person Classroom Training

110,000
64,451

  • IABAC® & NASSCOM® Certification
  • 8-Month | 700 Learning Hours
  • 120-Hour Classroom Sessions
  • 25 Capstone & 1 Client Project
  • Cloud Lab Access
  • Internship + Job Assistance

ARE YOU LOOKING TO UPSKILL YOUR TEAM ?

Enquire Now

UPCOMING DATA SCIENCE ONLINE CLASSES IN SANGLI

BEST DATA SCIENCE CERTIFICATIONS

The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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WHY DATAMITES INSTITUTE FOR DATA SCIENCE COURSE

Why DataMites Infographic

SYLLABUS OF DATA SCIENCE COURSE IN SANGLI

MODULE 1: DATA SCIENCE ESSENTIALS 

 • Introduction to Data Science
 • Evolution of Data Science
 • Big Data Vs Data Science
 • Data Science Terminologies
 • Data Science vs AI/Machine Learning
 • Data Science vs Analytics

MODULE 2: DATA SCIENCE DEMO

 • Business Requirement: Use Case
 • Data Preparation
 • Machine learning Model building
 • Prediction with ML model
 • Delivering Business Value.

MODULE 3: ANALYTICS CLASSIFICATION 

 • Types of Analytics
 • Descriptive Analytics
 • Diagnostic Analytics
 • Predictive Analytics
 • Prescriptive Analytics
 • EDA and insight gathering demo in Tableau

MODULE 4: DATA SCIENCE AND RELATED FIELDS

 • Introduction to AI
 • Introduction to Computer Vision
 • Introduction to Natural Language Processing
 • Introduction to Reinforcement Learning
 • Introduction to GAN
 • Introduction to Generative Passive Models

MODULE 5: DATA SCIENCE ROLES & WORKFLOW

 • Data Science Project workflow
 • Roles: Data Engineer, Data Scientist, ML Engineer and MLOps Engineer
 • Data Science Project stages.

MODULE 6: MACHINE LEARNING INTRODUCTION

 • What Is ML? ML Vs AI
 • ML Workflow, Popular ML Algorithms
 • Clustering, Classification And Regression
 • Supervised Vs Unsupervised

MODULE 7: DATA SCIENCE INDUSTRY APPLICATIONS

 • Data Science in Finance and Banking
 • Data Science in Retail
 • Data Science in Health Care
 • Data Science in Logistics and Supply Chain
 • Data Science in Technology Industry
 • Data Science in Manufacturing
 • Data Science in Agriculture

MODULE 1: PYTHON BASICS 

 • Introduction of python
 • Installation of Python and IDE
 • Python Variables
 • Python basic data types
 • Number & Booleans, strings
 • Arithmetic Operators
 • Comparison Operators
 • Assignment Operators

MODULE 2: PYTHON CONTROL STATEMENTS 

 • IF Conditional statement
 • IF-ELSE
 • NESTED IF
 • Python Loops basics
 • WHILE Statement
 • FOR statements
 • BREAK and CONTINUE statements

MODULE 3: PYTHON DATA STRUCTURES 

 • Basic data structure in python
 • Basics of List
 • List: Object, methods
 • Tuple: Object, methods
 • Sets: Object, methods
 • Dictionary: Object, methods

MODULE 4: PYTHON FUNCTIONS 

 • Functions basics
 • Function Parameter passing
 • Lambda functions
 • Map, reduce, filter functions

MODULE 1: OVERVIEW OF STATISTICS 

 • Introduction to Statistics
 • Descriptive And Inferential Statistics
 • Basic Terms Of Statistics
 • Types Of Data

MODULE 2: HARNESSING DATA 

 • Random Sampling
 • Sampling With Replacement And Without Replacement
 • Cochran's Minimum Sample Size
 • Types of Sampling
 • Simple Random Sampling
 • Stratified Random Sampling
 • Cluster Random Sampling
 • Systematic Random Sampling
 • Multi stage Sampling
 • Sampling Error
 • Methods Of Collecting Data

MODULE 3: EXPLORATORY DATA ANALYSIS 

 • Exploratory Data Analysis Introduction
 • Measures Of Central Tendencies: Mean,Median And Mode
 • Measures Of Central Tendencies: Range, Variance And Standard Deviation
 • Data Distribution Plot: Histogram
 • Normal Distribution & Properties
 • Z Value / Standard Value
 • Empirical Rule and Outliers
 • Central Limit Theorem
 • Normality Testing
 • Skewness & Kurtosis
 • Measures Of Distance: Euclidean, Manhattan And Minkowski Distance
 • Covariance & Correlation

MODULE 4: HYPOTHESIS TESTING 

 • Hypothesis Testing Introduction
 • P- Value, Critical Region
 • Types of Hypothesis Testing
 • Hypothesis Testing Errors : Type I And Type II
 • Two Sample Independent T-test
 • Two Sample Relation T-test
 • One Way Anova Test
 • Application of Hypothesis testing

 

MODULE 1: MACHINE LEARNING INTRODUCTION 

 • What Is ML? ML Vs AI
 • Clustering, Classification And Regression
 • Supervised Vs Unsupervised

MODULE 2:  PYTHON NUMPY  PACKAGE 

 • Introduction to Numpy Package
 • Array as Data Structure
 • Core Numpy functions
 • Matrix Operations, Broadcasting in Arrays

MODULE 3:  PYTHON PANDAS PACKAGE 

 • Introduction to Pandas package
 • Series in Pandas
 • Data Frame in Pandas
 • File Reading in Pandas
 • Data munging with Pandas

MODULE 4: VISUALIZATION WITH PYTHON - Matplotlib

 • Visualization Packages (Matplotlib)
 • Components Of A Plot, Sub-Plots
 • Basic Plots: Line, Bar, Pie, Scatter

MODULE 5: PYTHON VISUALIZATION PACKAGE - SEABORN

 • Seaborn: Basic Plot
 • Advanced Python Data Visualizations

MODULE 6: ML ALGO: LINEAR REGRESSSION

 • Introduction to Linear Regression
 • How it works: Regression and Best Fit Line
 • Modeling and Evaluation in Python

MODULE 7: ML ALGO: LOGISTIC REGRESSION

 • Introduction to Logistic Regression
 • How it works: Classification & Sigmoid Curve
 • Modeling and Evaluation in Python

MODULE 8: ML ALGO: K MEANS CLUSTERING

 • Understanding Clustering (Unsupervised)
 • K Means Algorithm
 • How it works : K Means theory
 • Modeling in Python

MODULE 9: ML ALGO: KNN

 • Introduction to KNN
 • How It Works: Nearest Neighbor Concept
 • Modeling and Evaluation in Python

MODULE 1: FEATURE ENGINEERING 

 • Introduction to Feature Engineering
 • Feature Engineering Techniques: Encoding, Scaling, Data Transformation
 • Handling Missing values, handling outliers
 • Creation of Pipeline
 • Use case for feature engineering

MODULE 2: ML ALGO: SUPPORT VECTOR MACHINE (SVM)

 • Introduction to SVM
 • How It Works: SVM Concept, Kernel Trick
 • Modeling and Evaluation of SVM in Python

MODULE 3: PRINCIPAL COMPONENT ANALYSIS (PCA)

 • Building Blocks Of PCA
 • How it works: Finding Principal Components
 • Modeling PCA in Python

MODULE 4:  ML ALGO: DECISION TREE 

 • Introduction to Decision Tree & Random Forest
 • How it works
 • Modeling and Evaluation in Python

MODULE 5: ENSEMBLE TECHNIQUES - BAGGING 

 • Introduction to Ensemble technique 
 • Bagging and How it works
 • Modeling and Evaluation in Python

MODULE 6: ML ALGO: NAÏVE BAYES

 • Introduction to Naive Bayes
 • How it works: Bayes' Theorem
 • Naive Bayes For Text Classification
 • Modeling and Evaluation in Python

MODULE 7: GRADIENT BOOSTING, XGBOOST

 • Introduction to Boosting and XGBoost
 • How it works?
 • Modeling and Evaluation of in Python

MODULE 1: TIME SERIES FORECASTING - ARIMA 

 • What is Time Series?
 • Trend, Seasonality, cyclical and random
 • Stationarity of Time Series
 • Autoregressive Model (AR)
 • Moving Average Model (MA)
 • ARIMA Model
 • Autocorrelation and AIC
 • Time Series Analysis in Python 

MODULE 2: SENTIMENT ANALYSIS 

 • Introduction to Sentiment Analysis
 • NLTK Package
 • Case study: Sentiment Analysis on Movie Reviews

MODULE 3: REGULAR EXPRESSIONS WITH PYTHON 

 • Regex Introduction
 • Regex codes
 • Text extraction with Python Regex

MODULE 4:  ML MODEL DEPLOYMENT WITH FLASK 

 • Introduction to Flask
 • URL and App routing
 • Flask application – ML Model deployment

MODULE 5: ADVANCED DATA ANALYSIS WITH MS EXCEL

 • MS Excel core Functions
 • Advanced Functions (VLOOKUP, INDIRECT..)
 • Linear Regression with EXCEL
 • Data Table
 • Goal Seek Analysis
 • Pivot Table
 • Solving Data Equation with EXCEL

MODULE 6:  AWS CLOUD FOR DATA SCIENCE

 • Introduction of cloud
 • Difference between GCC, Azure, AWS
 • AWS Service ( EC2 instance)

MODULE 7: AZURE FOR DATA SCIENCE

 • Introduction to AZURE ML studio
 • Data Pipeline
 • ML modeling with Azure

MODULE 8:  INTRODUCTION TO DEEP LEARNING

 • Introduction to Artificial Neural Network, Architecture
 • Artificial Neural Network in Python
 • Introduction to Convolutional Neural Network, Architecture
 • Convolutional Neural Network in Python

MODULE 1: DATABASE INTRODUCTION 

 • DATABASE Overview
 • Key concepts of database management
 • Relational Database Management System
 • CRUD operations

MODULE 2:  SQL BASICS

 • Introduction to Databases
 • Introduction to SQL
 • SQL Commands
 • MY SQL workbench installation

MODULE 3: DATA TYPES AND CONSTRAINTS 

 • Numeric, Character, date time data type
 • Primary key, Foreign key, Not null
 • Unique, Check, default, Auto increment

MODULE 4: DATABASES AND TABLES (MySQL) 

 • Create database
 • Delete database
 • Show and use databases
 • Create table, Rename table
 • Delete table, Delete table records
 • Create new table from existing data types
 • Insert into, Update records
 • Alter table

MODULE 5: SQL JOINS 

 • Inner Join, Outer Join
 • Left Join, Right Join
 • Self Join, Cross join
 • Windows function: Over, Partition, Rank

MODULE 6: SQL COMMANDS AND CLAUSES 

 • Select, Select distinct
 • Aliases, Where clause
 • Relational operators, Logical
 • Between, Order by, In
 • Like, Limit, null/not null, group by
 • Having, Sub queries

MODULE 7 : DOCUMENT DB/NO-SQL DB 

 • Introduction of Document DB
 • Document DB vs SQL DB
 • Popular Document DBs
 • MongoDB basics
 • Data format and Key methods

MODULE 1: GIT  INTRODUCTION 

 • Purpose of Version Control
 • Popular Version control tools
 • Git Distribution Version Control
 • Terminologies
 • Git Workflow
 • Git Architecture

MODULE 2: GIT REPOSITORY and GitHub 

 • Git Repo Introduction
 • Create New Repo with Init command
 • Git Essentials: Copy & User Setup
 • Mastering Git and GitHub

MODULE 3: COMMITS, PULL, FETCH AND PUSH 

 • Code Commits
 • Pull, Fetch and Conflicts resolution
 • Pushing to Remote Repo

MODULE 4: TAGGING, BRANCHING AND MERGING 

 • Organize code with branches
 • Checkout branch
 • Merge branches
 • Editing Commits
 • Commit command Amend flag
 • Git reset and revert

MODULE 5: GIT WITH GITHUB AND BITBUCKET

 • Creating GitHub Account
 • Local and Remote Repo
 • Collaborating with other developers

MODULE 1: BIG DATA INTRODUCTION 

 • Big Data Overview
 • Five Vs of Big Data
 • What is Big Data and Hadoop
 • Introduction to Hadoop
 • Components of Hadoop Ecosystem
 • Big Data Analytics Introduction

MODULE 2 : HDFS AND MAP REDUCE 

 • HDFS – Big Data Storage
 • Distributed Processing with Map Reduce
 • Mapping and reducing stages concepts
 • Key Terms: Output Format, Partitioners,
 • Combiners, Shuffle, and Sort

MODULE 3: PYSPARK FOUNDATION 

 • PySpark Introduction
 • Spark Configuration
 • Resilient distributed datasets (RDD)
 • Working with RDDs in PySpark
 • Aggregating Data with Pair RDDs

MODULE 4: SPARK SQL and HADOOP HIVE 

 • Introducing Spark SQL
 • Spark SQL vs Hadoop Hive

MODULE 1: TABLEAU FUNDAMENTALS 

 • Introduction to Business Intelligence & Introduction to Tableau
 • Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
 • Bar chart, Tree Map, Line Chart
 • Area chart, Combination Charts, Map
 • Dashboards creation, Quick Filters
 • Create Table Calculations
 • Create Calculated Fields
 • Create Custom Hierarchies

MODULE 2:  POWER-BI BASICS

 • Power BI Introduction 
 • Basics Visualizations
 • Dashboard Creation
 • Basic Data Cleaning
 • Basic DAX FUNCTION

MODULE 3 : DATA TRANSFORMATION TECHNIQUES 

 • Exploring Query Editor
 • Data Cleansing and Manipulation:
 • Creating Our Initial Project File
 • Connecting to Our Data Source
 • Editing Rows
 • Changing Data Types
 • Replacing Values

MODULE 4: CONNECTING TO VARIOUS DATA SOURCES 

• Connecting to a CSV File
 • Connecting to a Webpage
 • Extracting Characters
 • Splitting and Merging Columns
 • Creating Conditional Columns
 • Creating Columns from Examples
 • Create Data Model

OFFERED DATA SCIENCE COURSES IN SANGLI

DATA SCIENCE COURSE REVIEWS

ABOUT DATA SCIENTIST TRAINING IN SANGLI

DataMites, a globally recognized leader in data science training, is dedicated to empowering aspiring data professionals with comprehensive learning programs. Focused on experiential training, real-world applications, and career-focused assistance, DataMites has established itself as the preferred choice for data science courses in Sangli. The programs are designed to cater to learners at all levels, providing a robust foundation and advanced expertise.

The Certified Data Scientist Course in Sangli, accredited by IABAC and NASSCOM FutureSkills, is an extensive 8-month program tailored to meet global industry standards. Offering flexible learning formats, including online and on-demand offline data science courses in Sangli, this program balances theoretical insights with practical exposure. With industry-relevant projects and dedicated placement assistance, the course prepares participants whether fresh graduates or seasoned professionals to excel in the dynamic field of data science.

Data Science Training in Sangli: Your Pathway to a Flourishing Career

In today's data-driven world, the ability to analyze and extract valuable insights from vast datasets is essential. According to Future Market Insights, the data science sector is projected to experience a significant compound annual growth rate (CAGR) of 29% by 2033. The revenue share of the data science platform market is expected to grow from US$ 106.74 billion in 2023 to US$ 1,362.09 billion by 2033.

India, a leader in the data revolution, is seeing increased demand for data science professionals across industries such as healthcare, banking, e-commerce, and government services.

Sangli, known for its strong educational infrastructure and growing tech scene, is quickly becoming a prime location for data science training. Its proximity to major IT hubs like Pune, Kolhapur, and Bengaluru further enhances its appeal for aspiring data science professionals.

DataMites, a globally recognized training institute, offers high-quality data science courses in Sangli. The goal of these courses is to give students the tools they need to succeed in the rapidly changing data science industry.

Why Choose Sangli for Data Science Training?

Sangli blends its strong educational roots with a budding IT ecosystem, offering an ideal setting for data science training in Sangli. Here’s why Sangli stands out:

Growing IT Infrastructure

Sangli is gradually becoming a technology hub, supported by the presence of emerging IT firms and startups. Additionally, its closeness to Pune, Kolhapur, and Bengaluru renowned IT hubs opens doors to numerous career opportunities in data analytics and machine learning.

Rising Demand for Data Science Roles

There is a growing need for qualified data science specialists in Sangli. Job platforms such as LinkedIn and Naukri regularly list multiple data science job openings in Maharashtra. According to Indeed, the average salary for data scientists in Sangli is INR 5 LPA.

Cost-Effective Lifestyle

Compared to major metropolitan areas like Mumbai and Pune, Sangli offers an affordable living environment, making it an attractive destination for students and working professionals opting for data science courses in Sangli.

Educational Excellence

Sangli’s academic institutions and research centers provide a nurturing environment for professional growth. This strong foundation supports advanced learning, making it a preferred location for data science certification in Sangli.

Strategic Location and Connectivity

With seamless connectivity to cities like Pune, Kolhapur, and Belgaum, Sangli ensures easy access to broader career opportunities. The city’s calm yet modern ambiance creates the perfect atmosphere for immersive learning and skill development.

Prominent Data Science Careers and Key Skills in Sangli

As Sangli's IT sector continues to grow, a wide range of data science roles are emerging, offering exciting career prospects. Some of the prominent positions include:

  1. Data Scientist
  2. Machine Learning Engineer
  3. Data Analyst
  4. AI Specialist
  5. Business Intelligence Analyst

To succeed in these roles, aspiring professionals need to develop the following core skills:

  1. Programming Skills: Proficiency in languages such as Python, R, and SQL for data processing and analysis.
  2. Machine Learning Expertise: Strong knowledge of algorithms like Neural Networks, Decision Trees, and Gradient Boosting.
  3. Data Visualization: Expertise in tools such as Tableau, Power BI, and Matplotlib for effective data presentation.
  4. Big Data Technologies: Familiarity with platforms like Hadoop, PySpark, and MongoDB for handling large datasets.
  5. Mathematics and Statistics: A solid analytical foundation to solve complex problems and interpret data accurately.
  6. Soft Skills: Strong communication and critical thinking abilities to present findings and insights clearly.

Mastering these skills will help professionals excel in the thriving data science field in Sangli.

Why DataMites is the Top Choice for Data Science Training in Sangli

DataMites, a leading data science institute in Sangli, offers a comprehensive curriculum tailored to meet industry demands. Key features of our training program include:

  1. Global Certifications: Recognized by esteemed organizations such as IABAC and NASSCOM FutureSkills.
  2. Expert Instructors: Learn from experienced professionals in AI and data science, including Ashok Veda, our Lead Mentor, who brings extensive industry expertise and practical knowledge to the classroom.
  3. Flexible Learning Models: Options for live online classes and on-demand offline data science courses in Sangli.
  4. Practical Industry Exposure: 25 capstone projects and client assignments provide hands-on experience.
  5. Placement Support: A dedicated team assists with job placements, ensuring smooth transitions into roles such as Data Scientist and Machine Learning Engineer.

Innovative 3-Phase Learning Methodology at DataMites, Sangli

DataMites in Sangli offers a unique, structured approach to learning through its innovative 3-Phase Learning Methodology, designed to provide an immersive and practical educational experience.

Phase 1: Pre-Course Self-Study

Students kick-start their learning journey with curated video tutorials and study materials. This self-paced phase ensures a strong foundation in data science concepts before moving to more advanced topics.

Phase 2: Immersive Training

In this phase, students engage in 20 hours of intensive training per week for three months. They have the flexibility to choose between live online classes or on demand offline data science courses in Sangli. The curriculum is designed with hands-on projects, expert guidance, and industry-relevant content to ensure practical knowledge.

Phase 3: Internship & Placement Assistance

Students get the opportunity to work on 25 capstone projects, along with a real-world client project, to apply what they've learned. Upon completion, they earn a prestigious internship certification. DataMites' dedicated Placement Assistance Team (PAT) provides job search support, helping students land rewarding roles in leading companies.

Comprehensive Curriculum for Data Science Courses at DataMites, Sangli

DataMites offers an in-depth Certified Data Scientist Course in Sangli, covering a wide range of topics to ensure a well-rounded understanding of data science. Key components of the curriculum include:

  1. Python Programming: Master Python, along with key libraries like NumPy, Pandas, and Matplotlib, to build a strong foundation in data manipulation and analysis.
  2. Machine Learning: Gain expertise in popular machine learning algorithms, including Linear Regression, Decision Trees, and Neural Networks.
  3. Data Visualization: Learn to create impactful visualizations using tools such as Tableau and Power BI to present data insights effectively.
  4. Big Data Tools: Hands-on experience with big data technologies like PySpark, Hadoop, and Kafka, empowering students to manage and process large datasets.
  5. Artificial Intelligence: Dive into advanced AI topics such as Deep Learning, TensorFlow, and Natural Language Processing to explore cutting-edge innovations in the field.

Specialized Data Science Certifications at DataMites, Sangli

DataMites offers a range of specialized certifications tailored to meet specific career goals and domains. These include:

  1. Data Science for Managers: Designed for professionals in leadership roles, this course focuses on strategic decision-making using data-driven insights.
  2. Python for Data Science: A beginner-friendly course that provides a solid introduction to Python programming and data science fundamentals.
  3. Data Science in HR, Finance, and Marketing: Gain domain-specific expertise in applying data science to key business areas like HR, finance, and marketing.
  4. Diploma in Data Science: A comprehensive program aimed at preparing students for advanced roles in the field.

Practical Tools for Real-World Application

At DataMites, students in Sangli acquire proficiency in industry-standard tools used by professionals:

  1. Python, TensorFlow, and Pandas for data analysis, machine learning, and deep learning applications.
  2. Tableau, Power BI, and Advanced Excel for data visualization and reporting.
  3. PySpark, Hadoop, and MongoDB for working with big data and NoSQL databases.

This extensive curriculum equips learners with the skills and tools needed to succeed in data science careers in Sangli and beyond.

Internship and Placement Support in Sangli

The data science course in Sangli with internship offers hands-on exposure to real-world projects, enhancing technical and analytical skills. This practical experience bridges the gap between theory and industry applications, preparing learners for professional challenges.

Additionally, the data science course in Sangli with placement support includes resume-building workshops, mock interviews, and networking opportunities with top employers. This structured support ensures seamless career transitions.

Start Your Data Science Career in Sangli

Sangli is rapidly emerging as a growing hub for data science education, with a thriving tech scene, affordable living, and a strong academic foundation. Join the data science course in Sangli at DataMites to take advantage of placement and internship opportunities, hands-on training, real-world projects, and expert guidance.

DataMites also offers data science courses in Pune, Bangalore, Mumbai, Hyderabad, Chennai, Coimbatore, Delhi, Ahmedabad, and more. With comprehensive training and career support, DataMites helps you build a strong foundation for a successful data science career. Start your journey today by visiting DataMites in Sangli!

ABOUT DATAMITES DATA SCIENCE COURSE IN SANGLI

There is no specific qualification required to start a career in data science. However, having a background in mathematics, statistics, or computer science can be beneficial. Dedication and interest are the most important factors for learning data science.

The typical duration of a data science program in Sangli ranges from 4 to 12 months. It usually includes a mix of online classes, hands-on projects, and assignments to develop practical skills. The exact duration may vary based on the program and schedule.

The entry-level salary for a data scientist in Sangli typically ranges from INR 3 to  INR 7 lakhs per annum. This can vary based on the candidate's skills, experience, and the employing organization.

The future potential for data science professionals in Sangli is promising, with growing demand across industries such as finance, healthcare, and technology. Opportunities are expected to expand as more businesses leverage data for strategic decisions.

Several institutions in Sangli offer quality data science courses. DataMites stands out as a leading global institute, providing extensive internship opportunities, solid placement assistance, and globally recognized certifications, with over 70,000 satisfied alumni. Reviews and recommendations from alumni can also provide useful insights.

No, coding proficiency is not strictly required to start a career in data science, but having coding skills can be highly beneficial. Knowledge of programming languages like Python or R can help you perform data analysis, build models, and solve complex problems more effectively.

Yes, individuals without an engineering background can transition into data science by gaining relevant skills through courses, certifications, and practical experience. A strong foundation in mathematics and programming is helpful.

A data science course typically covers topics such as data analysis, statistical methods, machine learning, and data visualization. Courses also include practical exercises and projects to apply these skills.

A data scientist is someone who analyzes and interprets complex data to help organizations make informed decisions. They use statistical methods, machine learning, and data visualization techniques to solve problems and predict trends.

To learn data science effectively in Sangli, consider enrolling in local institutes or exploring online programs. DataMites offers a comprehensive data science course with hands-on projects and internship opportunities. Additionally, DataMites provides offline classes in cities like Bangalore, Pune, Chennai, and Mumbai, which can be an alternative if you're looking for in-person learning.

While no specific skills are mandatory, core skills for success in data science include proficiency in programming, statistical analysis, data visualization, and machine learning. Strong problem-solving abilities and a solid understanding of data manipulation are also crucial.

Yes, data science jobs remain in high demand due to the increasing importance of data-driven decision-making in various industries. This trend is expected to continue as organizations seek to leverage data for competitive advantage.

Data scientists often face challenges such as handling large volumes of data, ensuring data quality, and integrating data from diverse sources. They also need to stay updated with rapidly evolving tools and techniques.

Career opportunities in data science include roles such as data analyst, data scientist, machine learning engineer, and data engineer. Positions are available across sectors like finance, healthcare, and technology.

Key phases in a data science project include problem definition, data collection, data cleaning, exploratory data analysis, modeling, and evaluation. The final phase involves presenting the results and deriving actionable insights.

To begin a career as a data analyst in Sangli, start by acquiring relevant skills through courses or certifications. Build a portfolio with practical projects, and seek internships or entry-level positions to gain experience.

Commitment to studying a data science course varies by program, but dedicating 10-15 hours per week is a good starting point. This includes attending classes, completing assignments, and working on projects.

Data science is applied across industries for tasks like predictive modeling in finance, customer segmentation in marketing, and disease prediction in healthcare. It helps organizations make data-driven decisions and optimize operations.

Critical steps in a data science project include defining the problem, collecting and cleaning data, performing exploratory analysis, building and validating models, and communicating the results. Each step is crucial for deriving actionable insights.

While prior programming experience is beneficial, it is not strictly necessary to start a career in data science. Many courses teach programming skills, but having a basic understanding of coding can be advantageous.

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FAQ’S OF DATA SCIENCE TRAINING IN SANGLI

To enroll in DataMites Data Science course, visit their website and fill out the inquiry form. You will receive a call from our admissions team to discuss the details and complete the registration process. Payment options and schedule information will also be provided.

Yes, DataMites offers Data Science courses in Sangli that include 25 capstone projects and 1 client project. These live projects provide hands-on experience and help bridge the gap between theoretical knowledge and practical application.

Upon enrolling, you will receive comprehensive study materials, including course books, access to online resources, and software tools required for the course. You will also get access to recorded sessions and practice exercises.

The Data Science course from DataMites in Sangli includes the IABAC® and NASSCOM® FutureSkills certifications, among other relevant credentials based on course completion and performance. These certifications help validate your skills and enhance your career prospects in the field.

Yes, DataMites provides placement support as part of our Data Science courses in Sangli. This includes resume building, interview preparation, and job placement assistance to help you secure a position in the field.

Yes, DataMites provides internship opportunities as part of the Data Science course in Sangli. These internships offer practical experience to complement your learning and enhance your skills in real-world scenarios.

The fee for the DataMites Data Science course in Sangli ranges from INR 40,000 to INR 80,000, depending on the chosen learning mode and specific courses. For the most accurate information, please visit the DataMites website or reach out to the support team.

Ashok Veda, CEO of Rubixe, serves as the chief instructor at DataMites. The training staff is made up of extremely talented individuals with in-depth understanding of data science, who offer useful advice and insights gleaned from actual work experience.

Yes, DataMites offers demo classes to prospective students. This allows you to experience the course content and teaching style before making a final decision on enrollment.

Yes, DataMites provides options to make up missed sessions. You can access recorded classes or attend makeup sessions, ensuring you stay on track with your learning.

DataMites has a refund policy based on the timing of the cancellation and specific course terms. For detailed information, please review the refund policy provided during the enrollment process or contact our support team.

The Flexi-Pass provides 3 months of flexible access to DataMites courses, enabling learners to select and switch between various courses as needed. This option caters to different learning preferences and schedules, allowing for a customized educational experience. Enjoy the freedom to tailor your learning journey with ease.

Yes, DataMites offers EMI options for their Data Science training courses in Sangli, allowing you to pay the fees in manageable monthly installments. Additionally, other payment methods are available, including online payment, credit card, and debit card.

The Data Science syllabus at DataMites covers key topics such as data analysis, machine learning, statistics, data visualization, and programming languages like Python and R. The curriculum is designed to provide a comprehensive understanding of Data Science.

To enroll in the Certified Data Scientist course, visit the DataMites website, fill out the enrollment form, and follow the instructions provided. You will receive further details and assistance from their admissions team to complete the process.

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.

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