Data Science & AI , here is how they intersect.
Above is a graphic that demonstrates how these disciplines intersect with one another. Here you’ll see that ML is a subset of AI. Additionally, note that Data Science is its own distinct discipline with overlap/application in the fields of AI and ML, but not a subset of either.
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The entire program takes 4 months in full-time and 7 months in part-time commitment to complete
Fundamentals
Master both fundamental and advanced concepts in Python, encompassing the creation of basic variables, implementation of conditional logic, and utilisation of lists and dictionaries, among others.
Acquire proficiency in essential Data Science tools and techniques, including Pandas, Data Frames, Descriptive Statistics, Visualisations, Probability, and Distributions, to elevate your analytical capabilities.
SQL (Structured Query Language) is a standardised programming language used for managing and manipulating relational databases, enabling users to query, update, and delete data efficiently.
Learn to analyze data efficiently and create interactive visualizations using Excel. Master Power BI to build dynamic dashboards for insightful business decisions.
Supervised Learning
Understand the crucial steps in data cleaning, transformation, and feature engineering. Prepare datasets effectively for building accurate and robust AI models.
Dive into various algorithms to classify data into distinct categories. Explore real-world applications and techniques to improve model accuracy.
Discover methods to predict continuous variables and analyze relationships between data points. Apply regression techniques to solve business and research problems.
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Learn to measure and analyze the similarity between data points for recommendations. Implement similarity models to enhance clustering and classification tasks.
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Explore the ensemble learning technique of Random Forests to improve predictive performance. Understand how multiple decision trees work together for accurate results.
Gain insights into SVMs for handling classification and regression tasks. Learn to work with high-dimensional data for better model precision.
Unsupervised Learning
Master clustering algorithms to group similar data points and uncover hidden patterns. Apply clustering techniques to segment markets and analyze complex datasets.
Understand the fundamentals of neural networks and their architecture. Implement neural networks to solve complex problems in AI and Data Science.
Specializations
Learn tools and techniques for processing and analyzing massive datasets. Understand the challenges and solutions in handling big data effectively.
Analyze temporal data to identify trends, seasonality, and patterns. Use time series models to make accurate forecasts and informed decisions.
Explore Natural Language Processing techniques to process and understand human language. Apply NLP in text analysis, sentiment analysis, and language translation.
Get hands-on experience with TensorFlow and Keras to build deep learning models. Learn to deploy and optimize models for real-world applications.
Dive into advanced deep learning techniques, including CNNs and RNNs. Solve complex AI challenges with cutting-edge deep learning methods.
Interview Prep
Prepare for AI and Data Science job interviews with expert tips and strategies. Enhance your interview skills to land your dream job in the tech industry.
Learn how to effectively showcase your skills and experiences in behavioral interviews. Practice answering common behavioral questions to impress recruiters
Master technical interviews with practice problems and expert guidance. Understand key concepts and algorithms to succeed in technical assessments.
Build a strong LinkedIn presence to showcase your professional profile. Network effectively to connect with industry professionals and advance your AI career.
Frequently Asked Questions
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Access in depth learning programs across data science and artificial intelligence.
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