11-13 Months | 28 Projects
7-8 Months | 14 Projects
6-7 Months | 12 Projects
4.5 Months | 45 Projects
11-13 Months | 28 Projects
7-8 Months | 14 Projects
9-11 Months | 24 Projects
8-10 Months | 20 Projects
8-10 Months | 20 Projects
6-7 Months | 12 Projects
3-4 Months | 6 Projects
4.5 Months | 45+ Projects
3 Months | 30 Projects
Trainers from IIT, NIT and Top MNCs
Trainers from IIT, NIT and Top MNC’s
Our AI & Data Science course for managers provides extensive training in Python programming, covering Data Analytics, Web Scraping, Machine Learning, NLP, and Deep Learning. You’ll also learn Database Management System, Data Visualization with Power BI & Tableau, and version control with GitHub. Gain comprehensive knowledge and expertise in essential Data Science tools and techniques using Python through this course.
Our AI & Data Science course for managers provides extensive training in Python programming, covering Data Analytics, Web Scraping, Machine Learning, NLP, and Deep Learning. You’ll also learn Database Management System, Data Visualization with Power BI & Tableau, and version control with GitHub. Gain comprehensive knowledge and expertise in essential Data Science tools and techniques using Python through this course.
Benefits
The demand for data science in India is experiencing rapid growth, projected to increase by 200% by 2026. This surge presents a lucrative and appealing career option. Moreover, India holds the second position globally in recruiting data science talent, with the industry expected to reach USD 119 billion by 2026, generating a remarkable 11 million job openings.
Dual Certification
Be in demand with Microsoft certification
Gain advantage through real-world experience
GAIN ADVANTAGE THROUGH REAL-WORLD EXPERIENCE
Who This Program Is For?
Who This Program Is For?
Bachelor degree with good academic performance
Open to professionals with non-programming background
Early to mid-career professionals seeking data expertise
Striving for data-driven excellence and strategic optimization
Bachelor degree with good academic performance
Open to professionals with non-programming background
Early to mid-career professionals seeking data expertise
Striving for data-driven excellence and strategic optimization
Harness our influential industry network
Syllabus
Syllabus
1stepGrow offers a meticulously designed Data Science and Machine Learning course, providing hands-on learning opportunities through real-world projects and interactive live classes. With the assurance of job referrals, you can acquire practical experience and gain a competitive edge in the dynamic field of data and AI. Immerse yourself in this comprehensive program developed by industry experts to enhance your skills and knowledge in the industry..
1stepGrow offers a meticulously designed Data Science and Machine Learning course, providing hands-on learning opportunities through real-world projects and interactive live classes. With the assurance of job referrals, you can acquire practical experience and gain a competitive edge in the dynamic field of data and AI. Immerse yourself in this comprehensive program developed by industry experts to enhance your skills and knowledge in the industry..
Module 1: Introduction To Data Science, Analytics, Machine Learning & Artificial Intelligence
This course offers a comprehensive introduction to Git, a version control system, and GitHub, a popular platform for collaborative software development. Learn to effectively share and store work using these tools.
Introduction to Version Control Systems
Git Basics
Working with Git Remotely
Collaborating with GitHub
This course provides a comprehensive guide to optimizing your LinkedIn profile for professional success and networking opportunities.
Python is a versatile programming language widely used in data analytics and data science. With its rich libraries and frameworks like NumPy, Pandas, and scikit-learn, Python enables efficient data manipulation, analysis, and modelling, making it an essential tool for extracting insights from data.
NumPy
Pandas
Matplotlib
Seaborn
EDA Project
Analyze Data to Gain Insights and Identify Patterns – Use concepts like Remove duplicates, handle missing values, Calculate basic statistics like mean, median, and standard deviation to summarize the data. Create charts and graphs to visualize trends, patterns, and data behaviour.
Tools: Python: Jupyter Notebook – Pandas, NumPy, Matplotlib and Seaborn for analysis
Statistics and Machine Learning involve analyzing and interpreting data to gain insights and make predictions. Statistics focuses on data description, inference, and hypothesis testing, while Machine Learning involves developing algorithms and models to learn patterns and make predictions from data.
Time-Series Data Analysis involves studying data points collected over time to uncover patterns, trends, and seasonality. It is used in forecasting and predicting future values. Text Data Analysis involves processing and extracting insights from unstructured textual data, such as sentiment analysis, topic modelling, and text classification.
Deep Learning is a subset of machine learning that focuses on using artificial neural networks to model and understand complex patterns in data.
Database management involves the storage, organization, and retrieval of data. Structured databases use predefined schemas and are suitable for tabular data, while unstructured databases store data in flexible formats like text, images, and multimedia. Both are essential for efficient data management in various applications.
Introduction to SQL
SQL Basics
Advanced SQL Queries
Database Design and Normalization
Advanced Database Concepts
Introduction to MongoDB
MongoDB Basics
Advanced MongoDB Queries
MongoDB Administration
MongoDB and Programming Languages
Data Visualization is presenting data in visual formats such as charts, graphs, and maps to facilitate understanding and gain insights. We can use various tools. This course covers 3 of the most popular data visualization & analytics tools to add in your arsenal: Power BI, Tableau & Excel for Data Analytics
Introduction to Power BI
Data Preparation and Modeling
Data Visualization Techniques
Advanced Analytics in Power BI
Power BI Sharing and Collaboration
Introduction to Tableau
Data Preparation and Transformation
Building Visualizations in Tableau
Advanced Analytics in Tableau
Tableau Dashboards and Storytelling
Tableau Sharing and Collaboration
Introduction to Excel for Analytics
Data Preparation and Cleaning
Data Analysis Techniques in Excel
Advanced Excel Analytics
The process of collecting, storing, and processing large volumes of data from various sources to extract valuable insights. Tools like Hadoop, Spark, and Kafka enable efficient handling, analysis, and integration of big data for decision-making and data-driven applications.
The process of deploying machine learning models and data science applications on cloud platforms, enabling scalable and accessible solutions for real-time predictions and insights.
Introduction to Heroku
Deploying Machine Learning Models with Heroku
Monitoring and optimizing the deployed application
Module 1: Introduction To Data Science, Analytics, Machine Learning & Artificial Intelligence
This course offers a comprehensive introduction to Git, a version control system, and GitHub, a popular platform for collaborative software development. Learn to effectively share and store work using these tools.
Introduction to Version Control Systems
Git Basics
Working with Git Remotely
Collaborating with GitHub
This course provides a comprehensive guide to optimizing your LinkedIn profile for professional success and networking opportunities.
Python is a versatile programming language widely used in data analytics and data science. With its rich libraries and frameworks like NumPy, Pandas, and scikit-learn, Python enables efficient data manipulation, analysis, and modelling, making it an essential tool for extracting insights from data.
NumPy
Pandas
Matplotlib
Seaborn
EDA Project
Analyze Data to Gain Insights and Identify Patterns – Use concepts like Remove duplicates, handle missing values, Calculate basic statistics like mean, median, and standard deviation to summarize the data. Create charts and graphs to visualize trends, patterns, and data behaviour.
Tools: Python: Jupyter Notebook – Pandas, NumPy, Matplotlib and Seaborn for analysis
Statistics and Machine Learning involve analyzing and interpreting data to gain insights and make predictions. Statistics focuses on data description, inference, and hypothesis testing, while Machine Learning involves developing algorithms and models to learn patterns and make predictions from data.
Time-Series Data Analysis involves studying data points collected over time to uncover patterns, trends, and seasonality. It is used in forecasting and predicting future values. Text Data Analysis involves processing and extracting insights from unstructured textual data, such as sentiment analysis, topic modelling, and text classification.
Deep Learning is a subset of machine learning that focuses on using artificial neural networks to model and understand complex patterns in data.
Database management involves the storage, organization, and retrieval of data. Structured databases use predefined schemas and are suitable for tabular data, while unstructured databases store data in flexible formats like text, images, and multimedia. Both are essential for efficient data management in various applications.
Introduction to SQL
SQL Basics
Advanced SQL Queries
Database Design and Normalization
Advanced Database Concepts
Introduction to MongoDB
MongoDB Basics
Advanced MongoDB Queries
MongoDB Administration
MongoDB and Programming Languages
Data Visualization is presenting data in visual formats such as charts, graphs, and maps to facilitate understanding and gain insights. We can use various tools. This course covers 3 of the most popular data visualization & analytics tools to add in your arsenal: Power BI, Tableau & Excel for Data Analytics
Introduction to Power BI
Data Preparation and Modeling
Data Visualization Techniques
Advanced Analytics in Power BI
Power BI Sharing and Collaboration
Introduction to Tableau
Data Preparation and Transformation
Building Visualizations in Tableau
Advanced Analytics in Tableau
Tableau Dashboards and Storytelling
Tableau Sharing and Collaboration
Introduction to Excel for Analytics
Data Preparation and Cleaning
Data Analysis Techniques in Excel
Advanced Excel Analytics
The process of collecting, storing, and processing large volumes of data from various sources to extract valuable insights. Tools like Hadoop, Spark, and Kafka enable efficient handling, analysis, and integration of big data for decision-making and data-driven applications.
The process of deploying machine learning models and data science applications on cloud platforms, enabling scalable and accessible solutions for real-time predictions and insights.
Introduction to Heroku
Deploying Machine Learning Models with Heroku
Monitoring and optimizing the deployed application
Industry Projects
Industry Projects
Gain insights into public sentiment on financial news through sentiment analysis, aiding informed investment decisions. Apply data mining techniques to correlate news topics and exchanges with stock price movements for accurate short-term predictions in algorithmic trading strategies.
Perform a clinical trial project using a dataset on medicines’ usage, side effects, and substitutes. Analyze the effectiveness of different medications, identify potential side effects, and explore alternative treatment options. Apply statistical analysis and data visualization techniques to derive meaningful insights for improving patient care and optimizing medication strategies.
Leverage advanced analytics and machine learning techniques to analyze and interpret large datasets related to training programs at Crossfit. Examine various factors such as customers demographics, learning outcomes, instructional methods, and feedback and identify patterns, correlations, and insights that can inform evidence-based decision-making in designing and improving training programs.
Analyze various factors of student such as student demographics, past academic records, and engagement indicators to predict student performance that can provide personalized interventions for academic success using data science and machine learning techniques
Use machine learning and natural language processing techniques to analyze large datasets from websites to generate a comprehensive list of relevant keywords for optimizing search engine marketing campaigns.
Monitor and analyze equipment performance data from sensors, equipment logs, and historical maintenance records to identify potential issues, and proactively schedule maintenance activities to minimize downtime and improve operational efficiency.
Analyze historical load data, weather patterns, and other factors to accurately predict electricity demand that helps in planning energy distribution optimally. The project will help in planning resources, manage peak loads, and enhance overall energy efficiency.
Build a machine learning model to predict fares based on historical trip data factors like distance, duration, route, climate, time of travel, traffic conditions, demand-supply dynamics and surge pricing etc. The model should provide users with accurate fare estimates before confirming a ride.
Provide real-time insights and credibility ratings for news sources and articles by detecing the credibility of articles, social media posts, and online content using natural language processing (NLP) and machine learning algorithms. The tool should be able to distinguish between reliable and misleading information.
Wide Range Of Tools & Modules
What makes us Unique?
Generic program for freshers and working professionals.
Lack of schedule flexibility and alternative batch options.
Insufficient practical knowledge and no customization for professionals.
Fixed schedules that don't accommodate working professionals' needs.
Tailored by experts for industry relevance and confidence.
Practical approach to solving real-world problems with expert guidance.
Developed and delivered by top-tier industry experts for relevance and confidence.
Personalized doubt-clearing sessions, batch flexibility, and interactive live sessions.
Tailored by experts for industry relevance and confidence.
Practical approach to solving real-world problems with expert guidance.
Developed and delivered by top-tier industry experts for relevance and confidence.
Personalized doubt-clearing sessions, batch flexibility, and interactive live sessions.
Still Not Sure About The Course?
Avoid Confusion, Choose The Right Option That Suits Your Needs.
Still Not Sure About The Course?
Avoid Confusion, Choose The Right Option That Suits Your Needs.
Join live courses with two years of support and the freedom to switch between batches and instructors.
Access recorded classes for convenient review of missed sessions.
Receive personalized one-on-one doubt-clearing sessions addressing your specific questions and concerns.
Specially scheduled batches to accommodate working professionals.
Program Fee & Financing
Invest in your future with quality education
Financing as low as ₹5890/ month
Financing as low as ₹3924/ month
Financing as low as ₹5890/ month
Financing as low as ₹3924/ month
Still Not Sure About The Course?
Avoid Confusion, Choose The Right Option That Suits Your Needs.
Still Not Sure About The Course?
Avoid Confusion, Choose The Right Option That Suits Your Needs.
Thanks to 1stepGrow team, I am a successful Data Scientist. Transitioning from a teacher to the data science field was challenging, but the support and real-time project experience provided by 1stepGrow during the COVID pandemic made a significant difference. I am grateful for the personalized training and guidance from Ravi and the team. Today, I am proud to be working as a Data Scientist at Shyena Tech Yarn.
Coming from a mechanical background, I enrolled in 1stepgrow's data science program. The mentors provided exceptional support, helping me understand the concepts. Their guidance was invaluable, leading me to secure a job even before completing the program. The personalized attention and focused learning approach allowed me to ask multiple doubts and receive proper guidance.
My experience with 1stepGrow was fantastic. Their exceptional support enabled me to transition to the data science team in my company. Through hands-on work in the IT domain, I gained a deep understanding of the practical aspects of being a data scientist. The journey was seamless, thanks to the real-world experience provided by 1stepGrow.
1stepGrow is an excellent training institute for data science. Despite being a startup, I opted for them due to their small batch size. The vibrant class environment and interactive trainers greatly enhanced my skills. The encouraging atmosphere allowed me to ask questions and actively participate. Within just 6 months, I achieved success as a data analyst. My journey with 1stepGrow was truly amazing.
Learn More About Your Learning Options
The Foundational Data Science and Machine Learning Course is specifically designed for non-programmers and individuals from non-technical backgrounds. The course is beginner-friendly, starting from the basics, and is open to students with diverse backgrounds.
We offer two courses in the Foundation Data Science program:
Yes, this program is tailored for non-programmers looking to excel in the field of data science and machine learning. It is recommended for candidates with little to no prior knowledge of statistics and Python/R programming.
Our Data Science and Machine Learning Course focuses on providing high-quality training with a personalized touch. To ensure an optimal learning experience and encourage regular doubt-solving sessions, we maintain small batch sizes of up to 15 students. This enables mentors to provide individualized support and fosters interactive learning among participants.
Students enrolled in our Foundational Data Science and Machine Learning Course receive a 2-year subscription. This entitles them to ongoing access to live class support, mentorship from the institute, and job referrals for the duration of the subscription.
The online training program for the Foundational Data Science and Machine Learning Course provides students with several advantages:
The Data Science and Machine Learning Course has two options. The foundation data science and machine learning course has a duration of 4 months (120 hours), while the foundation PLUS data science and machine learning program lasts for 7 months (240 hours). Both options include live training sessions, hands-on training on live projects, and interview preparations. Classes are conducted on both weekdays and weekends. The weekday batch is held from Monday to Friday for 2 hours per day, and the weekend batch takes place on Saturdays and Sundays for 3.5 hours per day.
In the Data Science and Machine Learning Course, the instructor-led online training follows a structured format. Students engage in live sessions conducted by experienced trainers, allowing them to actively participate and interact with the instructor and peers. This training methodology facilitates the learning of foundational data science and machine learning concepts through practical exercises and real-world applications.
If you missed a live session in the Data Science and Machine Learning Course, there’s no need to worry. The instructor-led online training offers recorded sessions that you can access afterwards. This allows you to catch up on the missed content and stay on track with the course curriculum, ensuring that you don’t miss out on any valuable learning opportunities.
In the Data Science and Machine Learning Course, a smaller batch size plays a crucial role in improving the learning process. With a limited number of students, each individual can actively participate and have their questions addressed during the session. The trainer can devote ample time to explain concepts and ensure a thorough understanding of the course material.
Yes, students are encouraged to actively participate and ask questions during the live training sessions in the Data Science and Machine Learning Course. Our goal is to foster a collaborative learning environment, enabling students to engage with the trainer and seek clarification on any uncertainties. To facilitate effective interaction, we maintain small class sizes with a maximum of 15 students per batch.
The Foundational Data Science and Machine Learning Course builds a solid career foundation. Master concepts, statistical techniques, and programming skills in Python and SQL. Gain proficiency in data science libraries and frameworks. Unlock career prospects in finance, healthcare, e-commerce, and more by making data-driven decisions.
Yes, to assess your progress and understanding of the concepts taught, there will be periodic assessments and exams throughout the Foundational Data Science and Machine Learning Course. These evaluations are designed to ensure that you have a strong grasp of the topics covered and to help you identify areas that may require additional focus.
Yes, upon completing the Foundational Data Science and Machine Learning Course, you will receive lifetime access to the course materials. This includes recordings of the live sessions, class notes, assignments, and other learning resources. This ensures that you can refer back to the content whenever you need to revise or revisit any topic covered during the course.
Answer: Yes, the learning materials for the AI and Data Science Course for Managers, including recorded sessions, assignments, and course materials, are accessible through our online learning platform (LMS). This allows you to access the content on your mobile device, giving you the flexibility to learn on the go.
We understand that you may need to switch between batches if you miss an entire module or with any work commitment. If such a situation arises during the Foundational Data Science and Machine Learning Course, you can contact our support team, and they will assist you in making the necessary batch transfer arrangements, depending on the availability of seats in the desired batch.
During the Foundational Data Science and Machine Learning Course, you can expect comprehensive support from our team. This includes live class support, doubt-solving sessions, discussion forums, mentorship, and access to the learning materials. Our aim is to ensure that you have a smooth learning journey and that all your queries and concerns are addressed promptly.
Absolutely! The Foundational Data Science and Machine Learning Course emphasizes practical training to complement theoretical learning. Through practical exercises and real-world applications, you’ll develop the skills to extract insights from data and build predictive models. This hands-on experience will equip you with the necessary expertise to tackle data-driven challenges effectively.
Real-time projects in the Foundational Data Science and Machine Learning Course are based on industry data (with confidentiality protected) and offer students the opportunity to apply concepts and algorithms to actual datasets. These projects enhance the learning experience by providing practical exposure and allowing students to develop their skills in data science and machine learning. With 12 industry projects included in the course, students can gain hands-on experience and practice the techniques learned.
Answer: Domain specializations is part of Foundation PLUS Data Science and Machine Learning Course that provide industry-specific training through capstone projects and mentorship. These projects are sourced from diverse domains, allowing students to gain practical experience and apply data science and machine learning concepts in real-world scenarios. Domain specializations benefit students by deepening their understanding of data science in specific industries, preparing them for domain-specific challenges, and increasing their employability in the field of data science and machine learning.
The Foundational Data Science and Machine Learning Course includes 1 end-to-end Capstone projects. These projects provide students with the opportunity to apply their knowledge and gain practical experience by working on real-world scenarios in the domain of data science and machine learning.
Certainly! The Foundational Data Science and Machine Learning Course ensures that you have access to industry experts and mentors. These knowledgeable professionals will be there to support you, offer valuable insights, and provide mentorship as you dive into the fundamentals of data science and machine learning.
Yes! The Foundational Data Science and Machine Learning Course offers a community forum designed for students to interact and collaborate. Within this forum, you can engage in discussions, seek clarification on concepts, and work together on projects. It serves as a platform to connect with fellow learners, exchange ideas, and enhance your understanding of data science and machine learning foundations.
To address your queries outside the class, we provide a student forum exclusively for participants of the Foundational Data Science and Machine Learning Course. If you have any doubts or encounter difficulties while practicing, you can post your queries on the forum. Our trainers and fellow students actively participate on the forum, offering their expertise and insights to help you find solutions.
In the Foundational Data Science and Machine Learning Course, we understand the importance of resolving doubts and ensuring a strong foundation. Therefore, we conduct doubt-solving sessions within the class to address any questions or uncertainties that arise during the course. These sessions provide an opportunity for participants to seek clarification and gain a deeper understanding of the concepts covered.
The fees for foundation data science and machine learning course is INR 39,900/- + 18% GST.
The fees for the foundation PLUS data science and machine learning course is INR 59,900/- + 18% GST.
The different payment methods accepted by us are:
Yes, you can pay the fees in instalments by taking a no-cost EMI option for INR 3,924/month for a 12-month EMI (Foundation Data Science and Machine Learning Course) and INR 5,890/month for a 12-month EMI (Foundation PLUS Data Science and Machine Learning Course). You can choose an interest free loan by submitting Aadhar, PAN, 3-month salary slip and other required documents to our banking parner.
Yes! We provide installment options for course fee payment in the Foundational Data Science and Machine Learning Course. We understand that managing course fees is important, and we aim to support our students financially. You can connect with our admissions team to discuss the available payment plans and select the one that aligns with your financial needs.
1stepGrow offers 15 – 20% scholarship on early-birds. Our counselors will inform you if an early bird discount is available for the course.
Group discounts are available to promote ease in program fees. The discount applies to all members of a group who join the course together. For a group of 2, there is a 5% extra discount, and for a group of 3 or more, there is a 10% extra discount.
The Job Assistance program in the Foundational Data Science and Machine Learning Course is designed to help participants kick-start their careers in the field of data science and machine learning. Through this program, we provide job search support, resume building guidance, interview preparation, and networking opportunities. Our goal is to equip participants with the necessary skills and resources to secure job positions in the dynamic and rapidly growing field of data science and machine learning.
Our job assistance program is a four step program:
The mock interviews in the Foundational Data Science and Machine Learning Course are conducted online via video mode. Within a week, you will receive feedback on your performance. By reviewing the recorded video of the interview, you can identify areas for improvement in both soft skills and technical skills. This course offers up to 2 mock interviews.
Yes, we provide job assistance to students who have successfully completed the Foundational Data Science and Machine Learning Course. Our dedicated placement cell assists students in crafting effective resumes, preparing for interviews, and connects them with suitable job opportunities in the data science and machine learning domain. We are committed to helping our students achieve their career goals in this dynamic field.
Our Foundational Data Science and Machine Learning Course offers job referral assistance to our students until the end of the subscription period. We connect you with our network of partner companies and consultancies, increasing your chances of finding suitable job opportunities in the data science and machine learning field.
To be eligible for job assistance from 1stepGrow, you need to fulfill certain requirements. These include successfully completing all assessment tests with a score of 70% or higher, submitting assignments on time, completing real-time projects, and Capstone project.
Yes, upon successfully completing the Foundational Data Science and Machine Learning Course, you will receive a Course Completion Certificate from 1stepGrow. This certificate validates your proficiency in data science and machine learning, showcasing your skills to potential employers.
Yes, we provide academic certifications as part of the Foundational Data Science and Machine Learning Course. These certifications validate your knowledge and skills in the field of data science and machine learning, giving you a competitive edge in the job market. We are partnered with Microsoft. On successful completion of the assessment you will be awarded with a globally recognized Data certificate by Microsoft.
Our course offers you the opportunity to work on real-world projects in collaboration with our partner companies. Upon successful completion of these projects, you will receive a Project Experience Certificate, highlighting your practical skills and project-based learning.
As a college student or fresher, this course provides you with valuable recognition. You can expect a Course Completion Certificate that demonstrates your knowledge in data science and machine learning. On completion of course and real-time projects. The project experience gained during the course will also enhance your resume and increase your chances of securing internships and entry-level positions.
As an on-job professional, this course offers recognition that can propel your career forward. You will receive a Course Completion Certificate, validating your expertise in data science and machine learning. You will also be certified for the project experience and practical skills gained through completion of the capstone project. This will enhance your professional profile, enabling you to take on more challenging roles and responsibilities.
A project experience certification by a company holds significant value in the industry. It showcases your ability to apply data science and machine learning techniques to real-world projects, demonstrating your practical skills and problem-solving capabilities. This certification enhances your credibility and can make a positive impact on your career growth.
For working professionals we help our students specialize in domain by working on end-to-end industry projects. The projects will require implementation of concepts and tools you will be trained in the class. On successful completion of the project you will be awarded with a Project experience certificate by our collaborated company.
For college students / freshers, we help you work on an internship program for upto 6 months and get certified for the same.
Reach out to us and your career guide will get in touch with you shortly
The Foundational Data Science and Machine Learning Course is specifically designed for non-programmers and individuals from non-technical backgrounds. The course is beginner-friendly, starting from the basics, and is open to students with diverse backgrounds.
We offer two courses in the Foundation Data Science program:
Yes, this program is tailored for non-programmers looking to excel in the field of data science and machine learning. It is recommended for candidates with little to no prior knowledge of statistics and Python/R programming.
Our Data Science and Machine Learning Course focuses on providing high-quality training with a personalized touch. To ensure an optimal learning experience and encourage regular doubt-solving sessions, we maintain small batch sizes of up to 15 students. This enables mentors to provide individualized support and fosters interactive learning among participants.
Students enrolled in our Foundational Data Science and Machine Learning Course receive a 2-year subscription. This entitles them to ongoing access to live class support, mentorship from the institute, and job referrals for the duration of the subscription.
The online training program for the Foundational Data Science and Machine Learning Course provides students with several advantages:
The Data Science and Machine Learning Course has two options. The foundation data science and machine learning course has a duration of 4 months (120 hours), while the foundation PLUS data science and machine learning program lasts for 7 months (240 hours). Both options include live training sessions, hands-on training on live projects, and interview preparations. Classes are conducted on both weekdays and weekends. The weekday batch is held from Monday to Friday for 2 hours per day, and the weekend batch takes place on Saturdays and Sundays for 3.5 hours per day.
In the Data Science and Machine Learning Course, the instructor-led online training follows a structured format. Students engage in live sessions conducted by experienced trainers, allowing them to actively participate and interact with the instructor and peers. This training methodology facilitates the learning of foundational data science and machine learning concepts through practical exercises and real-world applications.
If you missed a live session in the Data Science and Machine Learning Course, there’s no need to worry. The instructor-led online training offers recorded sessions that you can access afterwards. This allows you to catch up on the missed content and stay on track with the course curriculum, ensuring that you don’t miss out on any valuable learning opportunities.
In the Data Science and Machine Learning Course, a smaller batch size plays a crucial role in improving the learning process. With a limited number of students, each individual can actively participate and have their questions addressed during the session. The trainer can devote ample time to explain concepts and ensure a thorough understanding of the course material.
Yes, students are encouraged to actively participate and ask questions during the live training sessions in the Data Science and Machine Learning Course. Our goal is to foster a collaborative learning environment, enabling students to engage with the trainer and seek clarification on any uncertainties. To facilitate effective interaction, we maintain small class sizes with a maximum of 15 students per batch.
The Foundational Data Science and Machine Learning Course builds a solid career foundation. Master concepts, statistical techniques, and programming skills in Python and SQL. Gain proficiency in data science libraries and frameworks. Unlock career prospects in finance, healthcare, e-commerce, and more by making data-driven decisions.
Yes, to assess your progress and understanding of the concepts taught, there will be periodic assessments and exams throughout the Foundational Data Science and Machine Learning Course. These evaluations are designed to ensure that you have a strong grasp of the topics covered and to help you identify areas that may require additional focus.
Yes, upon completing the Foundational Data Science and Machine Learning Course, you will receive lifetime access to the course materials. This includes recordings of the live sessions, class notes, assignments, and other learning resources. This ensures that you can refer back to the content whenever you need to revise or revisit any topic covered during the course.
Answer: Yes, the learning materials for the AI and Data Science Course for Managers, including recorded sessions, assignments, and course materials, are accessible through our online learning platform (LMS). This allows you to access the content on your mobile device, giving you the flexibility to learn on the go.
We understand that you may need to switch between batches if you miss an entire module or with any work commitment. If such a situation arises during the Foundational Data Science and Machine Learning Course, you can contact our support team, and they will assist you in making the necessary batch transfer arrangements, depending on the availability of seats in the desired batch.
During the Foundational Data Science and Machine Learning Course, you can expect comprehensive support from our team. This includes live class support, doubt-solving sessions, discussion forums, mentorship, and access to the learning materials. Our aim is to ensure that you have a smooth learning journey and that all your queries and concerns are addressed promptly.
Absolutely! The Foundational Data Science and Machine Learning Course emphasizes practical training to complement theoretical learning. Through practical exercises and real-world applications, you’ll develop the skills to extract insights from data and build predictive models. This hands-on experience will equip you with the necessary expertise to tackle data-driven challenges effectively.
Real-time projects in the Foundational Data Science and Machine Learning Course are based on industry data (with confidentiality protected) and offer students the opportunity to apply concepts and algorithms to actual datasets. These projects enhance the learning experience by providing practical exposure and allowing students to develop their skills in data science and machine learning. With 12 industry projects included in the course, students can gain hands-on experience and practice the techniques learned.
Answer: Domain specializations is part of Foundation PLUS Data Science and Machine Learning Course that provide industry-specific training through capstone projects and mentorship. These projects are sourced from diverse domains, allowing students to gain practical experience and apply data science and machine learning concepts in real-world scenarios. Domain specializations benefit students by deepening their understanding of data science in specific industries, preparing them for domain-specific challenges, and increasing their employability in the field of data science and machine learning.
The Foundational Data Science and Machine Learning Course includes 1 end-to-end Capstone projects. These projects provide students with the opportunity to apply their knowledge and gain practical experience by working on real-world scenarios in the domain of data science and machine learning.
Certainly! The Foundational Data Science and Machine Learning Course ensures that you have access to industry experts and mentors. These knowledgeable professionals will be there to support you, offer valuable insights, and provide mentorship as you dive into the fundamentals of data science and machine learning.
Yes! The Foundational Data Science and Machine Learning Course offers a community forum designed for students to interact and collaborate. Within this forum, you can engage in discussions, seek clarification on concepts, and work together on projects. It serves as a platform to connect with fellow learners, exchange ideas, and enhance your understanding of data science and machine learning foundations.
To address your queries outside the class, we provide a student forum exclusively for participants of the Foundational Data Science and Machine Learning Course. If you have any doubts or encounter difficulties while practicing, you can post your queries on the forum. Our trainers and fellow students actively participate on the forum, offering their expertise and insights to help you find solutions.
In the Foundational Data Science and Machine Learning Course, we understand the importance of resolving doubts and ensuring a strong foundation. Therefore, we conduct doubt-solving sessions within the class to address any questions or uncertainties that arise during the course. These sessions provide an opportunity for participants to seek clarification and gain a deeper understanding of the concepts covered.
The fees for foundation data science and machine learning course is INR 39,900/- + 18% GST.
The fees for the foundation PLUS data science and machine learning course is INR 59,900/- + 18% GST.
The different payment methods accepted by us are:
Yes, you can pay the fees in instalments by taking a no-cost EMI option for INR 3,924/month for a 12-month EMI (Foundation Data Science and Machine Learning Course) and INR 5,890/month for a 12-month EMI (Foundation PLUS Data Science and Machine Learning Course). You can choose an interest free loan by submitting Aadhar, PAN, 3-month salary slip and other required documents to our banking parner.
Yes! We provide installment options for course fee payment in the Foundational Data Science and Machine Learning Course. We understand that managing course fees is important, and we aim to support our students financially. You can connect with our admissions team to discuss the available payment plans and select the one that aligns with your financial needs.
1stepGrow offers 15 – 20% scholarship on early-birds. Our counselors will inform you if an early bird discount is available for the course.
Group discounts are available to promote ease in program fees. The discount applies to all members of a group who join the course together. For a group of 2, there is a 5% extra discount, and for a group of 3 or more, there is a 10% extra discount.
The Job Assistance program in the Foundational Data Science and Machine Learning Course is designed to help participants kick-start their careers in the field of data science and machine learning. Through this program, we provide job search support, resume building guidance, interview preparation, and networking opportunities. Our goal is to equip participants with the necessary skills and resources to secure job positions in the dynamic and rapidly growing field of data science and machine learning.
Our job assistance program is a four step program:
The mock interviews in the Foundational Data Science and Machine Learning Course are conducted online via video mode. Within a week, you will receive feedback on your performance. By reviewing the recorded video of the interview, you can identify areas for improvement in both soft skills and technical skills. This course offers up to 2 mock interviews.
Yes, we provide job assistance to students who have successfully completed the Foundational Data Science and Machine Learning Course. Our dedicated placement cell assists students in crafting effective resumes, preparing for interviews, and connects them with suitable job opportunities in the data science and machine learning domain. We are committed to helping our students achieve their career goals in this dynamic field.
Our Foundational Data Science and Machine Learning Course offers job referral assistance to our students until the end of the subscription period. We connect you with our network of partner companies and consultancies, increasing your chances of finding suitable job opportunities in the data science and machine learning field.
To be eligible for job assistance from 1stepGrow, you need to fulfill certain requirements. These include successfully completing all assessment tests with a score of 70% or higher, submitting assignments on time, completing real-time projects, and Capstone project.
Yes, upon successfully completing the Foundational Data Science and Machine Learning Course, you will receive a Course Completion Certificate from 1stepGrow. This certificate validates your proficiency in data science and machine learning, showcasing your skills to potential employers.
Yes, we provide academic certifications as part of the Foundational Data Science and Machine Learning Course. These certifications validate your knowledge and skills in the field of data science and machine learning, giving you a competitive edge in the job market. We are partnered with Microsoft. On successful completion of the assessment you will be awarded with a globally recognized Data certificate by Microsoft.
Our course offers you the opportunity to work on real-world projects in collaboration with our partner companies. Upon successful completion of these projects, you will receive a Project Experience Certificate, highlighting your practical skills and project-based learning.
As a college student or fresher, this course provides you with valuable recognition. You can expect a Course Completion Certificate that demonstrates your knowledge in data science and machine learning. On completion of course and real-time projects. The project experience gained during the course will also enhance your resume and increase your chances of securing internships and entry-level positions.
As an on-job professional, this course offers recognition that can propel your career forward. You will receive a Course Completion Certificate, validating your expertise in data science and machine learning. You will also be certified for the project experience and practical skills gained through completion of the capstone project. This will enhance your professional profile, enabling you to take on more challenging roles and responsibilities.
A project experience certification by a company holds significant value in the industry. It showcases your ability to apply data science and machine learning techniques to real-world projects, demonstrating your practical skills and problem-solving capabilities. This certification enhances your credibility and can make a positive impact on your career growth.
For working professionals we help our students specialize in domain by working on end-to-end industry projects. The projects will require implementation of concepts and tools you will be trained in the class. On successful completion of the project you will be awarded with a Project experience certificate by our collaborated company.
For college students / freshers, we help you work on an internship program for upto 6 months and get certified for the same.
Elevate your career with our courses – gain the skills and knowledge that will set you apart and propel you toward success. Check your eligibility now and enroll today. Let’s make your career dreams a reality.
We provide online certification in data science and AI, digital marketing, data analytics with a job guarantee program. For more information, contact us today!
Courses
1stepGrow
Anaconda | Jupyter Notebook | Git & GitHub (Version Control Systems) | Python Programming Language | R Programming Langauage | Linear Algebra & Statistics | ANOVA | Hypothesis Testing | Machine Learning | Data Cleaning | Data Wrangling | Feature Engineering | Exploratory Data Analytics (EDA) | ML Algorithms | Linear Regression | Logistic Regression | Decision Tree | Random Forest | Bagging & Boosting | PCA | SVM | Time Series Analysis | Natural Language Processing (NLP) | NLTK | Deep Learning | Neural Networks | Computer Vision | Reinforcement Learning | ANN | CNN | RNN | LSTM | Facebook Prophet | SQL | MongoDB | Advance Excel for Data Science | BI Tools | Tableau | Power BI | Big Data | Hadoop | Apache Spark | Azure Datalake | Cloud Deployment | AWS | GCP | AGILE & SCRUM | Data Science Capstone Projects | ML Capstone Projects | AI Capstone Projects | Domain Training | Business Analytics
WordPress | Elementor | On-Page SEO | Off-Page SEO | Technical SEO | Content SEO | SEM | PPC | Social Media Marketing | Email Marketing | Inbound Marketing | Web Analytics | Facebook Marketing | Mobile App Marketing | Content Marketing | YouTube Marketing | Google My Business (GMB) | CRM | Affiliate Marketing | Influencer Marketing | WordPress Website Development | AI in Digital Marketing | Portfolio Creation for Digital Marketing profile | Digital Marketing Capstone Projects
Jupyter Notebook | Git & GitHub | Python | Linear Algebra & Statistics | ANOVA | Hypothesis Testing | Machine Learning | Data Cleaning | Data Wrangling | Feature Engineering | Exploratory Data Analytics (EDA) | ML Algorithms | Linear Regression | Logistic Regression | Decision Tree | Random Forest | Bagging & Boosting | PCA | SVM | Time Series Analysis | Natural Language Processing (NLP) | NLTK | SQL | MongoDB | Advance Excel for Data Science | Alteryx | BI Tools | Tableau | Power BI | Big Data | Hadoop | Apache Spark | Azure Datalake | Cloud Deployment | AWS | GCP | AGILE & SCRUM | Data Analytics Capstone Projects
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