Data Science Training in Dharavi

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Learning Curve for Data Science

Learning curve for Data Science

Why Choose SevenMentor Data Science

Empowering Careers with Industry-Ready Skills.

Specialized Pocket Friendly Programs as per your requirements

Specialized Pocket Friendly Programs as per your requirements

Live Projects With Hands-on Experience

Live Projects With Hands-on Experience

Corporate Soft-skills & Personality Building Sessions

Corporate Soft-skills & Personality Building Sessions

Digital Online, Classroom, Hybrid Batches

Digital Online, Classroom, Hybrid Batches

Interview Calls Assistance & Mock Sessions

Interview Calls Assistance & Mock Sessions

1:1 Mentorship when required

1:1 Mentorship when required

Industry Experienced Trainers

Industry Experienced Trainers

Class Recordings for Missed Classes

Class Recordings for Missed Classes

1 Year FREE Repeat Option

1 Year FREE Repeat Option

Bonus Resources

Bonus Resources

Curriculum For Data Science

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Data Science Course

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Feb 15 - Feb 21

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Feb 22 - Feb 28

1 sessions
23
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Regular Batch

Mar 1 - Mar 7

1 sessions
02
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Regular Batch

Learning Comes Alive Through Hands-On PROJECTS!

Comprehensive Training Programs Designed to Elevate Your Career

Fake News Detection

Fake News Detection

Sales Forecasting Using Time Series Analysis(Data Science)

Sales Forecasting Using Time Series Analysis(Data Science)

Resume Screening System (Data Science)

Resume Screening System (Data Science)

Disease Prediction Using Patient Symptoms (Data Science)

Disease Prediction Using Patient Symptoms (Data Science)

Music Genre Classification(Data Science)

Music Genre Classification(Data Science)

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Course Content

About Data Science

Data Science is changing the digital landscape by converting raw data into valuable insights that drive corporate decisions, optimise processes, and forecast future trends. With the exponential increase in data output and the growing demand for data-driven strategies across all industries, there is a greater need than ever for skilled data science workers. To satisfy this growing need, Data Science Classes in Dharavi are now providing students, professionals, and enthusiasts with the necessary abilities to grasp this field.

Dharavi, recognised for its entrepreneurial energy and thriving activities, is quickly becoming a centre for digital literacy and new technology education. Recognising this trend, SevenMentor has built a complete data science training ecosystem that serves learners from all walks of life. This curriculum covers the fundamentals of programming as well as advanced machine learning and data visualisation.
 

Why Choose Data Science as a Career?

In today's technology landscape, data is a valuable asset. Organisations use data science to analyse trends, improve customer experiences, forecast revenues, and streamline processes. A career in data science not only offers significant earning potential, but also allows you to work on new and impactful initiatives. Career paths range from Data Analyst and Machine Learning Engineer to Data Scientist and AI Developer, making them both diverse and rewarding.

SevenMentor’s Data Science Courses in Mumbai provide opportunities for students and professionals who are interested in statistics, programming, and analytical thinking. The program is designed to prepare students for the workforce by combining academic knowledge with practical applications.
 

The Structure of Data Science Training in Dharavi

The curriculum covers both core and advanced data science subjects. It usually starts with basic Python and R programming, followed by statistical analysis, data manipulation, and data visualisation. As students proceed, they learn about machine learning algorithms, deep learning techniques, natural language processing, and big data technologies such as Hadoop and Spark.

These modules are supplemented with hands-on projects, case studies, and capstone assignments to ensure that students can apply theoretical principles in real-world circumstances. The course also covers popular technologies including Jupyter Notebooks, Pandas, NumPy, Matplotlib, Scikit-Learn, TensorFlow, Keras, Power BI, and Tableau.

By offering access to real-time datasets, industry mentors, and interactive labs, the Data Science training in Bombay ensures a rich and immersive learning experience. Whether you're a fresh graduate or an IT professional looking to upskill, this course helps you build a strong foundation in the data science ecosystem.
 

Real-World Project Experience

One of the distinguishing features of SevenMentor’s Data Science Classes in Dharavi is the emphasis on real-world projects. Learners develop end-to-end solutions that mimic industrial scenarios, such as fraud detection models, customer segmentation, sentiment analysis, demand forecasting, recommendation systems, and predictive maintenance. These initiatives not only put principles to the test in practice, but also boost confidence in using data to solve business problems.

The capstone project at the end of the semester acts as a full examination, with students expected to exhibit the abilities they learnt throughout the program. This involves issue conceptualisation, data collecting, data preparation, model development, model evaluation, and insight presentation.
 

Expert Faculty and Mentorship

Learning from experienced professionals is critical to learning data science. The training in Dharavi is delivered by qualified educators with extensive industry experience and academic credentials. The faculty comprises data scientists, AI researchers, and analytics consultants who offer practical knowledge to each class.

In addition to instructor-led instruction, students receive personalised mentorship and assistance. Mentors help with project development, résumé creation, interview preparation, and job recommendations. This collaborative and supportive environment encourages learners to stay motivated and goal-oriented.
 

Career Support and Placement Assistance

The ultimate goal of enrolling in Data Science Courses in Dharavi offered by SevenMentor is to build a successful career. To facilitate this, learners receive comprehensive career support that includes resume reviews, LinkedIn profile optimization, interview training, and mock assessments.

SevenMentor's placement team connects students to top firms in finance, healthcare, retail, e-commerce, and manufacturing. The numerous industry partnerships ensure that students have the opportunity to collaborate with reputable organisations on demanding data-driven projects. The institute's extensive alumni network is also a great source of advice and recommendations.
 

Tools and Technologies Covered

The Data Science training in Dharavi covers a wide range of tools and technologies used in the data science lifecycle. Learners get hands-on experience with the following programming languages: Python, R Data manipulation: Pandas, NumPy. Data Visualisation: Matplotlib, Seaborn, Tableau, and Power BI Databases: SQL, MongoDB; Machine Learning: Scikit-Learn, XGBoost, LightGBM; Deep Learning: TensorFlow, Keras. Big data tools include Apache Hadoop and Apache Spark, while cloud platforms include AWS, Google Cloud, and Azure (at the beginning level).

Learners become adept in designing and implementing data-driven models with these technologies after receiving organised instruction and practice sessions.
 

Certifications and Recognition

Upon successful completion of the course, students receive a certification that is recognized by industry employers. This certificate adds value to the resume and validates the candidate’s skills in data science. The certification covers core areas such as machine learning, data analysis, business intelligence, and data visualization.

Students also get the opportunity to prepare for global certifications such as Microsoft Certified Data Scientist, Google Professional Data Engineer, and IBM Data Science Professional Certificate.
 

About SevenMentor

SevenMentor is recognised as one of India's leading data science education organisations. With a proven track record of success, innovative teaching methods, and a learner-first approach, the institute has trained thousands of students in multiple cities.

SevenMentor, the best training institute for Data Science Training stands out for its commitment to quality, industry collaboration, and student success. The curriculum is regularly updated to reflect industry trends, and the institute ensures personalized attention through small batch sizes, interactive sessions, and hands-on labs.
 

Flexibility in Learning

One of the key advantages of enrolling in SevenMentor’s Data Science Classes in Dharavi is the flexibility it offers. Learners can choose from weekday, weekend, and fast-track batches based on their convenience. Working professionals can attend evening or weekend classes without disrupting their work schedule.

The institute also provides recorded sessions, access to learning material, and post-training support to ensure that learners can revisit and revise concepts at their own pace. These features make learning efficient, flexible, and personalized.

Data science is a game-changing field that affects every sector of the economy. Data science is one of today's most in-demand skills, with the capacity to drive innovation, find hidden trends, and improve decision-making.

Data Science Courses in Dharavi by SevenMentor offer a comprehensive and practical learning path to enter this high-growth field. With expert-led training, hands-on projects, personalized mentorship, and strong placement support, learners are equipped to thrive in the data science landscape.

 

Online Data Science Classes

SevenMentor offers robust and interactive online Data Science Classes in Dharavi. This mode of learning is designed for students, working professionals, and remote learners who want access to high-quality training without attending physical classes.

The online training follows the same curriculum and standards as classroom sessions. It includes live instructor-led sessions, doubt-clearing webinars, assignments, case studies, and project reviews. Students have access to a dedicated learning portal that houses all course content, session recordings, and downloadable resources. 

 

Corporate Data Science Training

SevenMentor also offers customized corporate Data Science training in Dharavi, designed to upskill employees and help organizations become data-driven. The corporate training program is customized to suit the business objectives, domain focus, and technical background of the team.

This training equips employees with skills in data analytics, machine learning, dashboarding, automation, and cloud-based data processing. Whether it's a finance team learning forecasting models or a marketing department analyzing customer behavior, the training adds immense value. The sessions are conducted onsite or online, depending on the client's preference. 

Frequently Asked Questions

Everything you need to know about our revolutionary job platform

1

Why is Data Science important?

Ans:
Data Science holds a significant place for several reasons: Better Decision Making: Analyzing data allows organizations to make informed, data-backed decisions instead of just relying on instinct or previous experiences. Business Growth: Data Science enables businesses to understand customer behavior, market movements, and operational performance, leading to better services, satisfied customers, and higher profits. Forecasting Trends: With predictive modeling, organizations can anticipate future demands, understand customer needs, and prevent potential risks. Customization: Data-driven insights allow companies to customize their marketing strategies and product recommendations to match individual customer preferences. Driving Innovation: Data Science plays a key role in innovation by optimizing workflows, discovering new possibilities, and identifying areas for enhancement. Scientific Progress: In areas like medical research, environmental science, and social studies, Data Science helps in analyzing huge datasets to make groundbreaking findings.
2

What is Data Science?

Ans:
Data Science is a multidisciplinary field that combines various techniques from statistics, maths, computer science, and industry expertise to extract useful information from data. The main goal of data science is to gather, process, study, and interpret large sets of data to discover hidden trends, patterns, and correlations. These insights help organizations and businesses to make better decisions. By using advanced algorithms and tools, data scientists can recognize valuable information that helps in improving efficiency, optimizing operations, and finding new growth opportunities.
3

Why is Data Science essential for the future?

Ans:
Data Science has gained immense significance in the past years due to the explosion of data generated from sources like social media, online shopping, and IoT devices. This massive data can be used to refine decision-making, enhance efficiency, and develop new services. Some key ways Data Science is shaping the future include- Predictive Models: Data Science builds models that forecast future events based on past data. This is used in sales predictions, fraud detection, and risk management. Machine Learning Applications: It enables machines to learn from data and make decisions without specific programming. This is useful in areas like voice recognition, natural language processing, and image detection. Data Visualization: Complex data can be turned into visual formats that make it easier to understand trends, spot patterns, and present information to stakeholders.
4

What skills are needed for Data Science?

Ans:
To become a successful data scientist, one must master a variety of skills. Some key skills required are: Programming Proficiency: Knowledge of languages like Python, R, or SQL is necessary for data analysis, manipulation, and visualization. Data Cleaning & Preprocessing: The ability to refine and structure unprocessed data to make it useful for analysis. Mathematics & Statistics: A strong grasp of statistics, probability, linear algebra, and calculus is important for effective data modeling. Machine Learning Expertise: Familiarity with classification, regression, clustering, and recommendation algorithms is crucial. Data Visualization: Being able to present insights clearly using tools like Tableau, Power BI, or libraries such as Matplotlib. Industry Knowledge: Understanding the field where data science is applied, like finance, healthcare, or manufacturing, improves the quality of insights. Collaboration Skills: Since data science often involves working in teams with engineers, analysts, and business stakeholders, teamwork is an important skill.
5

Which Programming Languages Are Required for Data Science?

Ans:
Programming plays a crucial role in data science as it helps in handling, analyzing, and interpreting large datasets. By using different programming languages and tools, data scientists can extract meaningful insights, make informed decisions, and solve challenging problems based on data. Some of the essential programming languages and skills for data science include: Python: One of the most widely used languages in data science due to its simplicity, flexibility, and a rich set of libraries. Libraries like NumPy, Pandas, Matplotlib, and Scikit-Learn make it easier to work with data, visualize patterns, and implement machine learning models. R: A programming language designed mainly for statistical analysis and data visualization. It provides a variety of statistical techniques and graphical tools, making it useful for research, reporting, and data analysis tasks. SQL: Structured Query Language (SQL) is essential for working with relational databases. Data scientists use SQL to query, retrieve, and manipulate data efficiently from large datasets stored in databases. Top Programming Languages for Data Science The most preferred languages for data science are Python and R due to their extensive capabilities. Python is a general-purpose language that is easy to learn and comes with a variety of libraries, including NumPy, Pandas, and SciPy. On the other hand, R is a statistical computing language with a vast collection of packages specifically designed for data analysis, visualization, and modeling. Other programming languages that are sometimes used in data science include Julia, SAS, and MATLAB. Julia is a high-performance language optimized for numerical computing. SAS is widely used in business analytics for handling large-scale statistical operations. MATLAB is known for its efficiency in numerical computing, especially in areas like signal and image processing. The choice of programming language in data science depends on the nature of the task. While Python and R are the most commonly used for general data science applications, Julia, SAS, and MATLAB serve specialized purposes.
6

Why Is Python Popular in Data Science?

Ans:
Python is an extremely versatile language that can be used for building different types of applications. It is widely favored in data science due to its straightforward syntax, ease of learning, and ability to work across different platforms. As an open-source language, Python has a vast and active developer community. It is a great choice for beginners due to its readable code structure and extensive learning resources. Additionally, its scalability and efficiency make it a preferred tool for professional data scientists. With strong industry adoption, Python remains a top choice for students and professionals entering the data science field. Importance of Data Science in Python Python is a widely used programming language in data science due to its flexibility, rich library ecosystem, and strong community support. Below are some key reasons why Python plays a crucial role in data science: Data Cleaning and Manipulation: Python provides powerful libraries such as NumPy and Pandas, which simplify data cleaning and manipulation tasks. These libraries allow users to handle large datasets efficiently by sorting, filtering, grouping, and restructuring data. Data Visualization: With libraries like Matplotlib, Seaborn, and Plotly, Python makes it easy to create engaging and interactive visualizations. These tools help data scientists interpret patterns, trends, and insights from data effectively. Machine Learning and AI: Python has an extensive collection of machine learning and artificial intelligence libraries, including TensorFlow, Scikit-learn, and PyTorch. These libraries provide advanced tools for building, training, and deploying predictive models, making data-driven decision-making easier. Natural Language Processing (NLP): Python is widely adopted for NLP tasks like text classification, sentiment analysis, and named entity recognition. Libraries such as NLTK and spaCy simplify text processing, enabling efficient analysis of unstructured data. Data Integration & Connectivity: Python supports seamless integration with different data sources, including SQL and NoSQL databases, APIs, and cloud storage platforms. This flexibility allows data scientists to aggregate and analyze information from multiple sources effortlessly. Python for Data Science and Machine Learning Python is a general-purpose, high-level programming language that has gained immense popularity in the fields of data science and machine learning. Its simplicity, versatility, and comprehensive libraries make it a preferred choice for professionals in these areas. Simplicity: Python’s clear and concise syntax makes it easy to learn, making it accessible to both beginners and experienced programmers. This allows data scientists to focus on solving analytical problems without being overwhelmed by complex code. Versatility: Python is not limited to a specific task—it can be used for data preprocessing, model development, and deployment. This makes it a valuable tool for handling diverse data science and machine learning projects. Extensive Library Support: Python’s rich ecosystem of libraries and frameworks makes it a powerful tool for data science. Libraries such as NumPy, Pandas, Scikit-learn, and TensorFlow provide a broad range of functionalities, from data visualization and manipulation to machine learning model development. Importance of R Programming in Data Science R programming plays a vital role in data science due to its specialized statistical capabilities and powerful data visualization features. Here’s why R is significant in this field: Open-Source & Community Support: Being an open-source language, R is freely available and supported by a vast community of users and developers. This collaborative environment continuously enhances R’s functionality, ensuring its relevance in evolving data science challenges. Comprehensive Statistical Analysis: R provides an extensive set of statistical and data analysis functions, making it a go-to tool for statisticians. It supports various techniques, including regression analysis, clustering, time-series forecasting, and hypothesis testing. Data Visualization Capabilities: R excels in data visualization with libraries like ggplot2, which is widely used for generating high-quality graphs and charts. These visual tools help in creating compelling data presentations and reports. Seamless Integration with Other Tools: R easily integrates with other programming languages such as Python, Java, and C++, allowing data scientists to leverage multiple tools for complex analysis. Machine Learning & AI: With specialized packages for machine learning and artificial intelligence, R supports predictive modeling, natural language processing, and data-driven decision-making in various industries. Essential Database Skills for Data Science SQL for Data Retrieval: Proficiency in SQL is fundamental for data science professionals. It is essential to know how to write optimized SQL queries for retrieving, filtering, aggregating, and joining data from relational databases. Understanding query execution plans is also crucial for improving performance. Database Design & Modeling: Database knowledge extends beyond just querying tables—it includes understanding entity-relationship (ER) diagrams, schema design, and data validation constraints. A well-structured database schema ensures efficient data storage and retrieval for analytical tasks.
7

What is Data Cleaning and Transformation?

Ans:
Data cleaning and transformation are essential steps for any data scientist to ensure raw data is in the proper format for analysis. It’s crucial to have skills in extracting data from multiple sources, converting it into the correct format, and then loading it into a database. Mastery of ETL tools, scripting languages like Python or R, and data transformation techniques is necessary for success in data science.
8

What is Database Optimization?

Ans:
Database optimization involves using various techniques to enhance database performance, such as creating indexes, denormalizing the structure, and leveraging caching mechanisms. Indexes, in particular, play a significant role in speeding up data retrieval. By adding indexes, the database engine can locate data more efficiently, leading to faster query responses.
9

How to Ensure Data Integrity and Quality?

Ans:
Maintaining data integrity is key to ensuring the accuracy and reliability of data. Various constraints, including unique, not null, and check constraints, are applied to prevent data errors. Additionally, using transactions ensures that multiple operations are handled as one, preventing partial updates and ensuring consistency.
10

Why is Integration with Tools and Languages Important for Data Scientists?

Ans:
To be successful, a data scientist must understand how to connect to databases and analyze data using programming languages like Python. Mastery of tools such as Python's pandas, R, and visualization libraries allows for effective data analysis and comprehensive presentation of findings. These tools enhance a data scientist's ability to draw meaningful insights from data.
11

What is Database Management and Storage in Data Science?

Ans:
In data science, managing and storing data is essential, especially when handling large datasets. Key components of this process include: Data Storage: Relational Databases like MySQL, PostgreSQL, and SQL Server are typically used for storing structured data. NoSQL Databases like MongoDB and Cassandra are ideal for handling unstructured or semi-structured data. Data Warehouses like Amazon Redshift and Google BigQuery are optimized for reporting and analytics tasks. Data Management: Data Cleaning ensures raw data is transformed into useful formats, involving tasks such as handling missing values and detecting outliers.
12

What Are the Key Tools for Database Management and Storage in Data Science?

Ans:
Two of the most important tools for managing and storing data in data science are MySQL and Hadoop. MySQL is a relational database management system that allows users to store, organize, and retrieve data efficiently. It is widely used for handling large datasets and is essential for data science tasks. Hadoop is a distributed computing framework ideal for processing and analyzing large datasets across multiple machines. It helps businesses and organizations handle vast amounts of data, enabling effective data management and insight extraction at scale.
13

How is Data Science Different from Data Analysis?

Ans:
Data science involves a wider range of activities than data analysis. It covers tasks such as collecting, organizing, cleaning, and interpreting data, in addition to developing and deploying machine learning models. These models can be used across many applications. Data analysis, however, is a more focused activity that revolves around exploring and visualizing data to identify trends and patterns that can assist with decision-making. While data analysis is an integral part of data science, it represents just one facet of the broader discipline.
14

Best Institute for Data Science in Pune?

Ans:
SevenMentor Institute is recognized as one of the top Data Science Training Institutes in Pune for the following reasons: The course offers a detailed overview of the entire Data Science Lifecycle, ensuring a well-rounded understanding of all aspects within the field. You will gain proficiency in analytics with Python and MySQL, equipping you with essential skills and knowledge to thrive in the industry. The Data Science course fees in Pune are competitive, providing great value for money and a solid investment in your career. In addition to the course, SevenMentor Institute offers webinars and more than 20 assignments, all designed to help you become job-ready.
15

Is This Course Suitable for Beginners?

Ans:
Yes, this course is designed with beginners in mind. SevenMentor Institute is recognized as one of the top Data Science Institutes in Pune, and it starts by teaching the fundamentals of mathematics and statistics. Students will also learn Python, the most commonly used programming language for data science.
16

What Are the Prerequisites for Enrolling in a Data Science Course?

Ans:
To enroll in this data science course, it is helpful to have a basic understanding of: Mathematics, including probability, statistics, algebra, and calculus. Object-oriented programming languages such as Java, C, or Python. Familiarity with data manipulation tools like SQL and Excel can also be an advantage. Good problem-solving and critical thinking skills are also recommended.
17

What Does the Curriculum of the Data Science Course Cover?

Ans:
The data science curriculum is designed to equip students with the skills needed to analyze and interpret large, complex datasets. The program usually includes: In-depth training in Python and other programming languages for data manipulation. Topics like data visualization, statistical analysis, machine learning, deep learning, and real-world projects that provide hands-on experience. By the course’s end, students are prepared to tackle complex data analysis challenges and make data-driven decisions.
18

What Programming Tools & Languages Are Covered?

Ans:
Data science involves several tools and languages that are essential for analyzing and interpreting data. Key tools include: Python and R: Both are widely used for their versatility and rich libraries in data analysis and manipulation. Visualization tools like Tableau and Power BI: These are used to create visual insights from data. SQL: A crucial tool for querying and retrieving data from databases. Machine learning libraries: These are used to build predictive models. These tools are necessary for data scientists to gather, manipulate, and derive meaningful insights from data.
19

Who Can Benefit from a Data Science Course?

Ans:
Anyone interested in working with data to extract valuable insights can benefit from this course, including: Students aiming for a career in data science. Working professionals from diverse fields such as IT, finance, healthcare, and more. Individuals considering a career change to data-related roles.
20

What Are the Job Prospects After Completing a Data Science Course?

Ans:
Data Science is a rapidly growing industry, and there is a high demand for skilled professionals. After completing the course, graduates can apply for roles such as: Data Analyst Data Scientist Machine Learning Engineer Business Intelligence Analyst And more, across various industries.
21

Can I Enroll in This Course After Completing My Degree?

Ans:
Yes, you can enroll in a data science program after completing your degree. SevenMentor Institute offers a program that provides hands-on experience through real industry projects, making it a great opportunity for recent graduates.
22

What Is the Expected Salary for a Fresher or Experienced Data Scientist in India?

Ans:
A fresher in Data Science can expect to earn an average salary of INR 5,00,000 annually. With experience, a Data Scientist can earn up to INR 6,00,000 or more, depending on their skills and job role.

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