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FREE Beginner-Friendly Courses to Learn AI.. To Change Your Future These are great to get you started in the AI field Offered by leaders in the field. AND they’re beginner friendly! We’re talking IBM, Deep Learning and Google: Check them out! No Payment required ✅ 🪢 7000+ Course Free Access : https://lnkd.in/gB83CKkZ <>. Google Data Analytics: 🔗https://lnkd.in/gFvFZmGa 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/grAwYaJA 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: - Learn Python and R, the most popular programming languages. - Master essential libraries like NumPy, Pandas, Matplotlib. - Learn how to use databases like SQL and MongoDB. Python: https://lnkd.in/gZqUJiBv R language: https://lnkd.in/gXkeqcAq SQL: https://lnkd.in/gGUkbrSZ MongoDB: https://lnkd.in/gF4VXs52 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: - Understand the fundamentals of probability and statistics. - Learn how to apply these concepts to real-world data problems. Probability: https://lnkd.in/gPi2udnG Statistics: https://lnkd.in/gafpTXih 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn the basics of machine learning, including model construction, data exploration, and validation. - Explore intermediate concepts like handling missing values, categorical variables. - Dive into ensemble learning techniques like Random Forests. 🪢 https://lnkd.in/g9tWNFsi 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn about artificial neural networks, convolutional neural networks, and recurrent neural networks. - Implement deep learning models using TensorFlow, or PyTorch. - Understand crucial concepts like stochastic gradient descent, dropout. 🪢 https://lnkd.in/gg2KYvv3 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: - Learn the art of feature engineering, from creating baseline models to encoding categorical variables, generating new features, and selecting the most impactful features for your models. Feature Engineering : https://lnkd.in/gpzKKdZj 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: - Learn how to deploy your data science models to production using cloud platforms like Microsoft Azure, or Google Cloud Platform. - Build web applications with Flask or Django. Microsoft Azure: https://lnkd.in/gw_ipaRp Google Cloud: https://lnkd.in/gF8Wj9jK Flask: https://lnkd.in/g8_xz5Hf Flask Project: https://lnkd.in/gD7Dt5xa Django: https://lnkd.in/g93PxEaj #datascience #datascienceroadmap #datascience
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FREE Beginner-Friendly Courses to Learn AI.. To Change Your Future These are great to get you started in the AI field Offered by leaders in the field. AND they’re beginner friendly! We’re talking IBM, Deep Learning and Google: Check them out! No Payment required ✅ 🪢 7000+ Course Free Access : https://lnkd.in/gB83CKkZ <>. Google Data Analytics: 🔗https://lnkd.in/gFvFZmGa 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/grAwYaJA 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: - Learn Python and R, the most popular programming languages. - Master essential libraries like NumPy, Pandas, Matplotlib. - Learn how to use databases like SQL and MongoDB. Python: https://lnkd.in/gZqUJiBv R language: https://lnkd.in/gXkeqcAq SQL: https://lnkd.in/gGUkbrSZ MongoDB: https://lnkd.in/gF4VXs52 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: - Understand the fundamentals of probability and statistics. - Learn how to apply these concepts to real-world data problems. Probability: https://lnkd.in/gPi2udnG Statistics: https://lnkd.in/gafpTXih 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn the basics of machine learning, including model construction, data exploration, and validation. - Explore intermediate concepts like handling missing values, categorical variables. - Dive into ensemble learning techniques like Random Forests. 🪢 https://lnkd.in/g9tWNFsi 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn about artificial neural networks, convolutional neural networks, and recurrent neural networks. - Implement deep learning models using TensorFlow, or PyTorch. - Understand crucial concepts like stochastic gradient descent, dropout. 🪢 https://lnkd.in/gg2KYvv3 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: - Learn the art of feature engineering, from creating baseline models to encoding categorical variables, generating new features, and selecting the most impactful features for your models. Feature Engineering : https://lnkd.in/gpzKKdZj 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: - Learn how to deploy your data science models to production using cloud platforms like Microsoft Azure, or Google Cloud Platform. - Build web applications with Flask or Django. Microsoft Azure: https://lnkd.in/gw_ipaRp Google Cloud: https://lnkd.in/gF8Wj9jK Flask: https://lnkd.in/g8_xz5Hf Flask Project: https://lnkd.in/gD7Dt5xa Django: https://lnkd.in/g93PxEaj #datascience #datascienceroadmap #datascience
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FREE Beginner-Friendly Courses to Learn AI.. To Change Your Future These are great to get you started in the AI field Offered by leaders in the field. AND they’re beginner friendly! We’re talking IBM, Deep Learning and Google: Check them out! No Payment required ✅ 🪢 7000+ Course Free Access : https://lnkd.in/eyyxZc5R <>. Google Data Analytics: 🔗https://lnkd.in/evAWmZSt 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/eEHETvJK 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: - Learn Python and R, the most popular programming languages. - Master essential libraries like NumPy, Pandas, Matplotlib. - Learn how to use databases like SQL and MongoDB. Python: https://lnkd.in/eQ2hDmwz R language: https://lnkd.in/eyEQ7Zpt SQL: https://lnkd.in/e-brcZws MongoDB: https://lnkd.in/ennPFtYn 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: - Understand the fundamentals of probability and statistics. - Learn how to apply these concepts to real-world data problems. Probability: https://lnkd.in/eb6pmWG5 Statistics: https://lnkd.in/esni6PqD 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn the basics of machine learning, including model construction, data exploration, and validation. - Explore intermediate concepts like handling missing values, categorical variables. - Dive into ensemble learning techniques like Random Forests. 🪢 https://lnkd.in/exZ9uekQ 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn about artificial neural networks, convolutional neural networks, and recurrent neural networks. - Implement deep learning models using TensorFlow, or PyTorch. - Understand crucial concepts like stochastic gradient descent, dropout. 🪢 https://lnkd.in/eW9cffig 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: - Learn the art of feature engineering, from creating baseline models to encoding categorical variables, generating new features, and selecting the most impactful features for your models. Feature Engineering : https://lnkd.in/epWWDVvg 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: - Learn how to deploy your data science models to production using cloud platforms like Microsoft Azure, or Google Cloud Platform. - Build web applications with Flask or Django. Microsoft Azure: https://lnkd.in/ejHd52HP Google Cloud: https://lnkd.in/eA8Z3PEi Flask: https://lnkd.in/ekTUqN23 Flask Project: https://lnkd.in/eXzDGaGu Django: https://lnkd.in/eUrY4w6q #datascience #datascienceroadmap #datascience
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FREE Beginner-Friendly Courses to Learn AI.. To Change Your Future These are great to get you started in the AI field Offered by leaders in the field. AND they’re beginner friendly! We’re talking IBM, Deep Learning and Google: Check them out! No Payment required ✅ 🪢 7000+ Course Free Access : https://lnkd.in/gFnFAkih <>. Google Data Analytics: 🔗https://lnkd.in/gHr2BEd4 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/gi9Hxx7d 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: - Learn Python and R, the most popular programming languages. - Master essential libraries like NumPy, Pandas, Matplotlib. - Learn how to use databases like SQL and MongoDB. Python: https://lnkd.in/g6Qs6ESn R language: https://lnkd.in/gbqtxwcK SQL: https://lnkd.in/ghQaaFZM MongoDB: https://lnkd.in/gSw48-X3 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: - Understand the fundamentals of probability and statistics. - Learn how to apply these concepts to real-world data problems. Probability: https://lnkd.in/gP573knX Statistics: https://lnkd.in/gJ92_TuK 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn the basics of machine learning, including model construction, data exploration, and validation. - Explore intermediate concepts like handling missing values, categorical variables. - Dive into ensemble learning techniques like Random Forests. 🪢 https://lnkd.in/gHnJ8zin 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn about artificial neural networks, convolutional neural networks, and recurrent neural networks. - Implement deep learning models using TensorFlow, or PyTorch. - Understand crucial concepts like stochastic gradient descent, dropout. 🪢 https://lnkd.in/gpzsjRgY 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: - Learn the art of feature engineering, from creating baseline models to encoding categorical variables, generating new features, and selecting the most impactful features for your models. Feature Engineering : https://lnkd.in/gyDdYSnm 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: - Learn how to deploy your data science models to production using cloud platforms like Microsoft Azure, or Google Cloud Platform. - Build web applications with Flask or Django. Microsoft Azure: https://lnkd.in/gdK8Qi3Q Google Cloud: https://lnkd.in/gCibKjdz Flask: https://lnkd.in/g_qVPZXR Flask Project: https://lnkd.in/gxYkcefS Django: https://lnkd.in/gFPN9j3J #python #sql #django #machinelearning #googlecloud #deeplearning #flask
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FREE Beginner-Friendly Courses to Learn AI.. To Change Your Future These are great to get you started in the AI field Offered by leaders in the field. AND they’re beginner friendly! We’re talking IBM, Deep Learning and Google: Check them out! No Payment required ✅ 🪢 7000+ Course Free Access : https://lnkd.in/eyyxZc5R <>. Google Data Analytics: 🔗https://lnkd.in/evAWmZSt 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/eEHETvJK 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠: - Learn Python and R, the most popular programming languages. - Master essential libraries like NumPy, Pandas, Matplotlib. - Learn how to use databases like SQL and MongoDB. Python: https://lnkd.in/eQ2hDmwz R language: https://lnkd.in/eyEQ7Zpt SQL: https://lnkd.in/e-brcZws MongoDB: https://lnkd.in/ennPFtYn 𝐏𝐫𝐨𝐛𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: - Understand the fundamentals of probability and statistics. - Learn how to apply these concepts to real-world data problems. Probability: https://lnkd.in/eb6pmWG5 Statistics: https://lnkd.in/esni6PqD 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn the basics of machine learning, including model construction, data exploration, and validation. - Explore intermediate concepts like handling missing values, categorical variables. - Dive into ensemble learning techniques like Random Forests. 🪢 https://lnkd.in/exZ9uekQ 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: - Learn about artificial neural networks, convolutional neural networks, and recurrent neural networks. - Implement deep learning models using TensorFlow, or PyTorch. - Understand crucial concepts like stochastic gradient descent, dropout. 🪢 https://lnkd.in/eW9cffig 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: - Learn the art of feature engineering, from creating baseline models to encoding categorical variables, generating new features, and selecting the most impactful features for your models. Feature Engineering : https://lnkd.in/epWWDVvg 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭: - Learn how to deploy your data science models to production using cloud platforms like Microsoft Azure, or Google Cloud Platform. - Build web applications with Flask or Django. Microsoft Azure: https://lnkd.in/ejHd52HP Google Cloud: https://lnkd.in/eA8Z3PEi Flask: https://lnkd.in/ekTUqN23 Flask Project: https://lnkd.in/eXzDGaGu Django: https://lnkd.in/eUrY4w6q #datascience #datascienceroadmap #datascience
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