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- AI/ Data science Training
Learn the latest in Data Science and AI with hands-on training from seasoned professionals in Raipur. Stay ahead of advancements and unlock new career opportunities—no prior experience is needed!
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Join Ionots’ live, instructor-led Data Science Course in Raipur and transform into a skilled Data Science professional in just 6 months! This comprehensive, hands-on program is designed to equip you with the most in-demand data science skills, making it one of the top-rated courses in the city.
Masterclasses Led by Distinguished Faculty and Top Industry Experts
3 Months (Weekdays)
Online
Placement Guidance
100+ Companies
Exposure to Practical Projects
Live Online Classes + Lifetime access to recorded videos
Learn with an Expert-Designed Curriculum Develop the skills that top companies are looking for, with hands-on projects and real-world applications
In this module, we will dive into the significance of Excel as a powerful data management tool, emphasizing the importance of structured data organization and efficient data manipulation techniques. Our exploration will cover Excel’s data structures, including tables and named ranges, alongside best practices for
enhancing data accessibility and analysis.
In this module, we will go through the importance of MySQL as a relational database management system, examining its architecture and the essential role of data types in optimizing database performance. We will navigate through the various data types supported by MySQL, including numeric, string, and date/time types, while also highlighting the importance
of efficient data storage and retrieval techniques.
In this module, we are going to cover the significance of Power BI for data visualization and business intelligence, focusing on its capabilities in data modelling, interactive reporting, and efficient data management techniques. Through this exploration, we will highlight the importance of utilizing star schemas for optimal data organization and the role of DAX (Data Analysis Expressions) in enhancing data analysis and reporting efficiency.
Now, in this module, we will delve into the significance of Python programming, focusing on its role in algorithmic thinking and the development of efficient coding practices. Our exploration will encompass essential data structures and algorithms, alongside effective memory management techniques tailored for Python.
In this module, we will dive into the significance of Data Structures and Algorithms (DSA) using Python, emphasizing the importance of efficient coding practices. Our exploration will cover various data structures, algorithmic strategies, and essential memory management techniques to optimize performance and resource utilization in Python applications.
In this module, we are going to cover the significance of Pandas for data manipulation and analysis, emphasizing its role in handling structured data efficiently. We will navigate through its key functionalities, including data frames, series, and data cleaning techniques, while also exploring the integration of Pandas with other libraries for enhanced data processing capabilities.
In this module, we will go through the importance of NumPy in scientific computing, emphasizing its role in efficient data manipulation and numerical analysis. We will navigate through its powerful array structures, explore vectorized operations, and understand memory management techniques that enhance performance in large-scale computations.
In this module, we will dive into the significance of data visualization and the necessity of effective graphical representation, focusing on three powerful libraries: Matplotlib, Seaborn, and Plotly. We will navigate through their unique features, exploring how Matplotlib serves as a foundational tool for static plots, Seaborn enhances aesthetic appeal for statistical graphics, and Plotly enables interactive visualizations that engage users in data exploration.
In this module, we will go through the importance of Probability, examining its fundamental concepts and applications. We will navigate through key topics such as probability distributions, conditional probability, and statistical inference.
In this module, we are going to cover the importance of Statistical Analysis and the necessity of data interpretation, exploring Descriptive and Inferential Statistics along with Probability Theory and Hypothesis Testing.
Now, in this module, we will delve into the significance of Supervised Machine Learning, examining its role in predictive modelling and classification tasks. We will navigate through key concepts such as labelled data, training and testing processes, and various algorithms used for supervised learning.
In this module, we will dive into the significance of Ensemble Learning and its role in enhancing predictive accuracy. By combining multiple models, we can effectively address the limitations of individual learners, thereby improving performance across various applications, including classification and regression tasks. Through techniques such as bagging, boosting, and stacking, we will explore how ensemble methods leverage diverse algorithms to minimize bias and variance, resulting in more robust and reliable predictions.
In this module, we are going to cover the significance of feature selection and parameter tuning, emphasizing their roles in enhancing model performance. We will navigate through various techniques for feature selection, including filter, wrapper, and embedded methods, while also exploring effective strategies for parameter tuning to optimize our machine learning models
In this module, we will go through the importance of Unsupervised Learning, exploring its applications in pattern recognition and data clustering, while examining key techniques such as k-means clustering and hierarchical clustering.
Now, in this module, we will delve into the significance of Recommendation Systems, emphasizing their role in personalizing user experiences. This exploration will cover the underlying principles of collaborative filtering and content-based filtering, alongside the implementation of machine learning algorithms to enhance prediction accuracy and user satisfaction.
In this module, we will dive into the significance of Neural Networks and the transformative role of Deep Learning in modern AI, examining how these technologies enable machines to learn from vast amounts of data, recognize patterns, and make informed decisions across various applications.
In this module, we are going to cover the significance of Computer Vision, emphasizing its role in transforming visual data into actionable insights. Our exploration will encompass key techniques such as image acquisition, feature extraction, and object recognition, alongside advanced methodologies like deep learning and convolutional neural networks (CNNs). Additionally, we will address the challenges of scene understanding and motion analysis, highlighting the necessity of robust algorithms for effective visual interpretation and real-world applications.
In this module, we will go through the importance of Natural Language Processing (NLP) and its vital role in understanding and generating human language. We will navigate through key concepts such as linguistic models, machine learning techniques, and the intricacies of semantic analysis, all while emphasizing the importance of effective communication and data interpretation in NLP applications.
In this module, we are going to cover the significance of Generative AI and its transformative impact on various industries, exploring its capabilities in content creation, automation, and decision-making processes. Additionally, we will examine how Generative AI enhances productivity and fosters innovation by leveraging advanced machine learning techniques and data synthesis.
In this module, we will dive into the significance of Prompt Engineering and its critical role in optimizing interactions with generative AI models. This exploration will encompass the techniques for crafting effective prompts, the impact of structured instructions on AI output quality, and the necessity of understanding user intent to enhance AI responsiveness and relevance.
Follow these simple steps to start your journey in data science today
Complete the Registration Form:
Provide your details, including your name, email, and educational background.
Profile Review:
Our dedicated counselors will review your profile to ensure the best fit for our programs.
Receive Approval:
Once your application is approved, you’ll receive a confirmation email with next steps to kickstart your learning journey!
Access expert guidance, resume reviews, and interview preparation to help you land your dream job in data science.
Tap into a network of top employers and opportunities tailored for data science professionals.
Get real-time guidance and insights from seasoned professionals to navigate your career path.
Optimize your job applications with tailored feedback to enhance your professional presence.
Gain invaluable insights and advice from leaders at the forefront of data science and analytics.
The future of data science is in its ability to empower businesses to make smarter, data-driven decisions. pskilling in this space is no longer optional but essential for career growth.
The Bootcamp includes around 500 hours of learning spread across 6 months. We expect you to put in around 15 hours of work on the weekends throughout the duration of the Bootcamp. The time commitment will be toward live classes, team tasks, assignments, quizzes, and project work.
In this Data Science Bootcamp, you will work on around 10+ projects across the core domains of Data Science. Projects are kept updated in line with industry trends; so expect variety
No prior hands-on experience in AI or Machine Learning is required to begin. Typically,
eligible applicants are final-year graduates in science, engineering, or related fields, or
working professionals seeking to transition into AI or enhance their skill set in this area.
All classes are conducted online over the internet using video conferencing solutions like Zoho Webinar / Webex. You will require access to the internet (2 Mbps+ recommended) on a computer (preferred) or on a mobile device to attend. Class size may vary depending on the specific cohort. However, we have teaching assistants available to interact in small groups and also conduct one-on-one sessions.
To speak with a counsellor for personalized guidance or career counselling, you can reach
us at 90003 02102 or email info@ionots.com. Our team is ready to assist you with any
questions regarding courses, career pathways, and enrolment requirements.
Yes it is affordable you can reach
us at 90003 02102 or email info@ionots.com. Our team is ready to assist you.
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