Freelance Data Science & AI Trainer

0 - 31 years

3 Lacs

Posted:3 weeks ago| Platform: Apna logo

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On-site

Job Type

Full Time

Job Description

Job Title: Freelance Data Science & AI Trainer Job Type: Freelance / Contract Job Description: We are looking for an experienced Data Science & AI Trainer to deliver comprehensive training on data science, machine learning, deep learning, and related technologies. The trainer will be responsible for conducting interactive sessions, guiding learners through practical projects, and ensuring strong conceptual understanding aligned with industry needs. Key Responsibilities: Deliver high-quality training on Data Science, Python Programming, Machine Learning, Deep Learning, and AI concepts. Teach foundational topics such as Excel-based EDA, Statistics, and Python for Data Science. Conduct sessions on Supervised Machine Learning, including regression, classification, model evaluation, and regularization techniques. Provide hands-on training in Feature Engineering, Model Tuning, and Dimensionality Reduction techniques. Train students on Deep Learning concepts including ANN, CNN, RNN, and LSTMs using frameworks like Tensor Flow and Keras. Guide participants through Capstone Projects, helping them with EDA, preprocessing, model selection, evaluation, and deployment. Support learners with career readiness, including mock interviews, resume building, and LinkedIn optimization. Create and share assignments, assessments, and project guidelines for practical learning. Ensure learners understand real-world applications of Data Science & AI by using case studies and industry examples. Required Skills & Expertise: Strong proficiency in Python programming, including Numpy, Pandas, Matplotlib, and Seaborn. Solid understanding of statistical concepts, hypothesis testing, and data visualization. Expertise in Machine Learning algorithms, model evaluation, and tuning techniques. Hands-on experience with Deep Learning frameworks (TensorFlow, Keras). Knowledge of data preprocessing, feature engineering, and dimensionality reduction methods. Familiarity with model deployment and visualization tools (e.g., Streamlit, dashboards). Ability to explain complex concepts in a simplified and engaging manner.

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