Data Science Course
Data Science Training in Pune
Data Science Training and courses for beginners at Tech Bunny Pune is the stupendous program containing a variety of Data Analytics and Data Science Training techniques. Our Data Science Training in Pune is truly outstanding, both in terms of content and the delivery provided by our world-class faculty. Data Science classes masters important like Data Science concepts such as Data Preprocessing, Exploratory Data Analytics, Data handling Techniques, Statistics, Algebra, maths, Machine Learning algorithms include regression, classification, and clustering. The Data Science course in Pune Assists individuals to get ready by working on real-time-case studies and equipping them to work independently on relevant projects.
Looking for affordable data science course fees in Pune? Explore data science classes near me and enroll in a top-rated data scientist course in Pune for hands-on learning and career growth.
Lectures: 100+
Duration: 175+ hours
Mode of Training: Online
About the Course
Learn from Industry Certified Professionals
Since an inauguration day of Tech Bunny, we helped thousands of individuals to become the job-ready on a highly demanded skill in the IT industry i.e. Data Science. Our data science course is crisp and contains many projects which really help the attendees to get sufficient knowledge to crack any interview they applied for. Our adept Trainers are providing expert training on either Weekends or Weekdays. Tech Bunny is a leading Online Coaching in Pune having a great track record providing a solid grip on Data Science from scratch.
Data Science Course is designed by industry mentors from various MNC’s, after many rounds of discussion we came up with a comprehensive data science syllabus which completely focused on practical and project-based learning. Data Science training in Pune provides an end to end understanding of technology and helps students to build a great foundation on the subject. Attendees will be prepared with interview questions from day1 and it will help to crack Data Science interviews and possess advanced knowledge of data science concepts.
What is Data Science? Who is a Data Scientist?
Let’s start discussing the Data science course in Pune with “What is Data Science”?
Data Science is the process of analysing and interpreting the hidden patterns, insights, and trends which are encrypted inside the data. Data Science can be interpreted as the study of data which is generated from a variety of sources, and how this information can be turned into a piece of valuable information that can fuel the decision-making process in business.
Who is Data Scientist? A Data Scientist is a professional who works extensively with raw, structured, and unstructured data to derive valuable business insights from it. A data scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data.
A Data Scientist enhances business decision making by introducing greater speed and better direction to the entire process with the help of their data visualization capabilities. Compared to data analysts, data scientists are much more technical and possess expertise in at least one programming language – R/Python, data extraction, data wrangling, data transformation, and loading capabilities.
Top Data Science Jobs for the year 2020 compiles of Data Scientist, Machine Learning Engineer, Machine Learning Scientist, Artificial Intelligence, Data Architect, Data Engineer, Data Analyst with an average of INR 700,000 salary.
Why one should take Data Science Course?
“The job of a data scientist has only grown sexier,” said Andrew Flowers, an economist at Indeed, based in Austin, Texas. “More employers than ever are looking to hire data scientists.”
With the surge in data (Calling Big Data) and its correlated fields, the job of a Data Scientist has become the most sought after job. To handle vast amounts of data produced every day, enterprises need professionals who can treat, analyze, and organize this data to provide valuable business insights, for intelligent actions. Data Science has emerged as the most promising field in recent times.
The demand for data scientists is only increasing and will continue to increase in the future. According to IBM, an increment between 200,000 to 600,000 openings will be generated in the year 2020. This demand will only grow further to an astonishing 700,000 openings.
According to Glassdoor, Data Scientist is the number one job on its website. This position will remain unchanged in the future. The requirement for the number of data scientists is growing at an exponential rate due to the increase in data and its various types. The number of roles and data scientists will only increase in the future. Some of the positions in data science such as data engineer, data science manager & big data architect. Moreover, the financial, telecom, retail, and insurance industries are becoming major players for recruiting data scientists.
The January report from Indeed, one of the top job sites, showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013 — a dramatic upswing. But while demand — in the form of job postings — continues to rise sharply, searches by job seekers skilled in data science grew at a slower pace (14%), suggesting a gap between supply and demand and the site considers data science a “high-demand skill.”.
Accessibility of the data today can help organizations to reap multiple benefits from it. Because of this, companies are not shying away from offering increased data scientist salary in India. Companies are offering huge salaries at those having skills to take on the positions of Data Analysts, Scientists, Engineers, etc. India is the second-highest country to recruit employees in the field of data science or data analytics, etc. with 50,000 positions available – second only to the United States.
What is the scope of Job Opportunities With Data Science Training?
Career opportunities in data have exponentially grown in the recent few years. India is the second-highest country to recruit employees in the field of data science or data analytics, etc. with 50,000 positions available.
If you have completed the certification course in data science from Tech Bunny, your career as a data scientist is expected to grow onwards and upwards.
The different job roles in Data Science which you can apply after the completion of your Data Science training certification are
- Data Scientist– Gathering vast amounts of structured and unstructured data and converting them into actionable insights. An encouraging data-driven approach to solving complex business problems.
Average salary: Rs 7,00,000 per annum
- Data Engineer- The primary job of a Data Engineer is to design and engineer a reliable infrastructure for transforming data into such formats as can be used by Data Scientists. In an organization, the position of a Data Engineer is as vital as that of a Data Scientist.
Average Salary: Rs 1,000,000 per annum
- Data Analyst- Data Analysts are professionals who translate numbers, statistics, figures, into plain English for everyone to understand.
Average Salary: Rs 6,00,000 per annum
By completing the Certification Course with Tech Bunny you may likely receive an annual bump up of around 15% in your compensation. This will further increase with an increase in the years of work experience and the number of skills you’ve mastered.
Why Choose Tech Bunny for Data Science ?
This Data Science Training In Pune is an ideal choice for all the analytics career enthusiasts who are planning to secure their careers in Data Science. As the course complements the present industry requirements, both fresher’s & working professionals who are looking towards a career shift from their existing technologies to Data Science can get enrolled for our Data Science Course In Pune. If you are new to programming & stats then there’s nothing to worry about, we have got you covered. Our Data Science training will cover the concepts right from the scratch. You will learn the basics of Statistics, Maths, SQL, EDA, Statistical analysis, Python programming to advanced AI, Machine Learning, Business Analytics & Predictive Analytics, Text Analytics and more.
Our Data Science training is the best fit for
- Managers
- Data analysts
- Business analysts
- Database Administrators
- Networking Operators
- Professional whats to change their career path
- Legacy Technologies Professional
- IT Developers & Software Professionals
- Job Seekers
- Freshers/Graduates
- End users
With the increasing demand for big data analytics, Data Science has become the key technology & the major buzz word across the IT & Corporate domain. So, this is the right time to step into this technology. Throughout this Data Science Training In Pune program, our expert trainers & mentors will be extending their full support to the participants. With a coordinated effort in our Data Science Training, we will be working towards transforming our students into complete career ready Data Scientists
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Industry Oriented Syllabus
Data Science Training Content
Applied Statistics
Maths Essentials
- Foundational Maths for DS:
- Introduction to Linear Algebra
- Theory of Matrices
- Determinant of a Matrix
- Eigenvalues and Eigenvectors
- Advanced Maths for DS:
- Calculus
- Differentiation
- Integration
- Maxima and Minima using derivatives
- Partial Derivatives
- Foundational Maths for DS:
Descriptive Statistics
- Probability Theory:
- Introduction to probability theory
- Conditional probability and Bayes theorem
- Random variables and properties
- Data Summarization:
- Introduction to data summarization
- Descriptive statistics and its uses
- Measures of central tendency
- Percentile and quartiles
- Skewness and kurtosis
- Outlier detection and treatment
- Discrete Probability Distributions:
- Probability mass function
- Cumulative distribution function
- Distribution
- Continuous Probability Distributions:
- Probability density function
- Cumulative distribution function
- Distribution
- Joint Distribution Concept:
- Joint probability mass function
- Joint probability density function
- Covariance and correlation
- Multivariate normal distribution
- Probability Theory:
Mastering Inferential Statistics
- Sampling & Statistical Inference:
- Introduction to Sampling
- Probability Sampling
- Non-Probability Sampling
- Sampling Bias and Estimation
- Sample Size Determination and Sum of Independent Random Variables
- Concept of Confidence:
- Introduction to Confidence Levels
- Interpreting Confidence Intervals
- Choosing Appropriate Confidence Levels
- Hypothesis Testing:
- Hypothesis
- Null and Alternative Hypotheses
- Type I and Type II Errors
- One-Tailed and Two-Tailed Tests
- P-Values
- Experimental Design:
- Experimental Design
- Types of Experimental Design
- Hypothesis Testing
- Power Analysis
- Ethical Considerations
- Sampling & Statistical Inference:
Relational Databases
Introduction to SQL: Learn the Lang. of Data
- SQL Basics for Data Analysis:
- Introduction to SQL
- Setting up the SQL environment
- Basic SQL Commands
- Creating and Deleting Databases and Tables
- Importing and Exporting Data from CSV Files
- Fundamentals of SQL Query:
- Anatomy of SQL Query
- SQL Data Types and Operators
- Filtering and Sorting Data in SQL
- Aggregate functions in SQL
- Dealing With Multiple Tables:
- Grouping Data – GROUP BY
- HAVING
- Subqueries
- Joining tables using INNER JOIN, LEFT JOIN, RIGHT JOIN & FULL OUTER JOIN
- Alias in SQL queries
- Working with Multiple Tables Using Subqueries
- Using Set Operators
- Aggregating Data from Multiple Tables using GROUP BY and HAVING.
- Advanced SQL Joins:
- Advanced Join Techniques
- Joining multiple tables
- Handling duplicate records and eliminating duplicates
- Using UNION and UNION ALL to combine data from multiple tables
- SQL Basics for Data Analysis:
SQL In-Built Functions
- Type Casting & Math Functions:
- Mathematical Functions
- Type Conversion Functions
- Using CASE Statements to Perform Conditional Operations
- DateTime & String Functions:
- Working with date/time data in SQL
- Date/time functions
- Formatting date/time data
- String manipulation functions (e.g. UPPER, LOWER, LEFT, RIGHT, etc.)
- Regular expressions in SQL for string operations
- Using CONCAT_WS to concatenate strings with a separator
- Window Functions:
- Syntax of Windows Function
- Ranking functions (e.g. ROW_NUMBER, RANK, DENSE_RANK, etc.)
- Aggregate functions using windows (e.g. SUM, AVG, MAX, MIN, etc.)
- Partitioning data for window functions
- Understanding the difference between row-based and aggregate-based window functions
- Type Casting & Math Functions:
Machine Learning & AI
Unlocking Machine Learning
- Learning Objective:
- Introduction to ML
- Supervised and Unsupervised Algorithms
- Understand the Mechanisms Behind Machine Learning
- Mechanisms Behind Machine Learning:
- Introduction to mechanism of Supervised
- Unsupervised and Deep Learning
- Supervised Learning – Regression:
- What are supervised models?
- What is regression analysis?
- Types of Regression Models
- Supervised Learning – Classification:
- Introduction to Supervised Models – Classification
- Logistic Regression
- What is logistic regression?
- Implementing logistic regression
- Evaluation Metrics used for Classification
- Defining the cost function
- Decision Trees:
- What is a Decision Tree?
- How to split?
- Math Behind it
- Simple Implementation
- Advantages & Disadvantages
- Unsupervised Learning:
- What is Unsupervised Learning?
- Introduction to Clustering
- K-Means Clustering
- Simple Example
- Expectation-Maximization
- Silhouette Analysis
- Elbow Method
- Implementation of K-Means
- Limitations
- Learning Objective:
Deep Learning, NLP & GenAI
Deep Learning aka gateway for AI
- Neural Networks:
- Introduction to Neural Networks
- Forward Propagation
- Back Propagation
- Optimizer
- Loss Function
- Activation Function
- Neural Networks:
Deep Learning aka gateway for AI
- Introduction to NLP:
- Introduction to Tokenization & Word-Embeddings
- RNN (Recurrent Neural Network):
- Introduction to RNNs
- RNN Architecture
- Training RNNs
- Applications of RNNs
- Advantages and Limitations
- Practical Examples
- Case Studies
- LSTM (Long Short-Term Memory):
- Introduction to LSTMs
- LSTM Architecture
- Training LSTMs
- Applications of LSTMs
- Advantages and Limitations
- Practical Examples
- Case Studies
- Gated Recurrent Unit (GRU):
- Introduction to GRU
- GRU vs LSTM
- GRU Architecture
- Advantages of GRU
- Implementation of GRU
- Introduction to NLP:
Generative AI (GenAI)
- The GenAI Revolution:
- Live demonstrations of AI capabilities (text, code, image generation)
- Real-world applications across industries (entertainment, healthcare, business)
- Interactive segment: Hands-on experience with basic AI tools
- Personalized AI Applications: From Concept to Reality:
- Personalized AI application on Ecommerce/Retail, etc.
- Interactive workshop: Building personalized AI solutions
- Technical Foundations: From User to Creator:
- API integration fundamentals
- Advanced prompt engineering techniques
- Customization and fine-tuning strategies
- Performance optimization and scaling strategies
- Hands-on workshop: Building an AI-powered application
- Career Pathways:
- Essential skills and knowledge domains
- Freelancing opportunities in AI development
- Interview preparation and industry requirements
- Guide to advanced learning resources and certifications
- The GenAI Revolution: