LearnBay Data Science Course Review
Today we are about to review the Data Science Course from the LearnBay platform, it offers various courses in the domain of Data Science. But today we are about to explore the course which is designed for you to get a job (Others are higher studies related)
Stay glued to know everything about this platform and course before taking it up or rejecting it.
This Advanced Data Science and AI program is designed for professionals seeking to advance their careers in the fast-changing field. They emphasize hands-on learning, industry knowledge, and real-world examples, encompassing statistics, data mining, and programming languages. Additionally, the program covers generative AI modules, enhancing your skills in this cutting-edge field. We also incorporate ethical aspects, providing an advantage to professionals in the job market.
Work in an industry-like environment with hands-on data science experience and dedicated industry mentors
Gain top-notch skills for a successful career through our degree and certification program
| Term | Module | Topics Covered |
|---|---|---|
| Prep | Preparatory Session | Programming basics, Anaconda, Jupyter, Python fundamentals, Git, GitHub, math review |
| 1 | Basic Python | Python programming, coding challenges, data types, functions, file I/O, exceptions, regex, data analysis, visualization |
| Advanced Python | Advanced Python, data preprocessing, logistic regression, classification metrics, KNN, decision tree, random forest, case studies | |
| 2 | Statistics | Fundamentals of math, probability, population & sample, descriptive & inferential statistics, hypothesis testing, linear algebra |
| Machine Learning | Machine learning algorithms, hyperparameter tuning, clustering, PCA, SVM, case studies, real-time projects | |
| 3 | SQL | SQL, RDBMS, NoSQL, MongoDB, data visualization, data cleansing, joins, subqueries, aggregation, dashboard creation |
| Tableau | Visual analytics, custom geocoding, polygon maps, WMS, background images | |
| MongoDB | MongoDB structures, shell vs server, data formats, working with Compass, schema design | |
| Big Data Analytics | Hadoop, Spark, R-Spark, MapReduce, time series analysis, ARIMA, multivariate analysis, forecasting | |
| 4 | Deep Learning | TensorFlow, neural networks, data preparation, model training & evaluation, AWS & Azure deployment |
| Natural Language Processing (NLP) | NLP basics, text analysis, ChatGPT, fine-tuning, DALL·E, image generation, ethical considerations | |
| AI Generative Tools & Future Trends | Midjourney, future AI trends, generative modeling, Graph Neural Networks (GNN), real-world GNN applications | |
| Bonus | Python Bootcamp for AI | Python essentials, flow control, syntax, variables, loops, LLMs, GPT-3, Copilot, personalized news recommendation, interview automation bot |
| Visual AI for eCommerce | Visual AI principles, style, photography, DALL-E, multimodal models, AI for customer service, digital transformation | |
| Intelligent News Aggregator | NLP history, neural network evolution, knowledge discovery, LangChain, Azure OpenAI, responsible AI, bias, fairness, future trends | |
| Customer Support Bot – HelpMate Pro | Project architecture, semantic search, embeddings, fine-tuning, OpenAI services, scaling strategy, MCQ assessment |
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