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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/dj4BPN7C <>. Google Data Analytics: 🔺https://lnkd.in/d75gurYD 📌𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: 🧊 https://lnkd.in/dWerQU2z 📌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/dVXmehyD R language: 🧊 https://lnkd.in/dcPD64QX SQL: 🧊https://lnkd.in/dqdN2Km5 MongoDB: 🧊 https://lnkd.in/dQRBMAuj 📌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/dA4WQiSM Statistics: 🧊 https://lnkd.in/dqe5BiWW 📌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/dqWJzVZY 📌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/dbisy3En 📌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/d3hArpnD 📌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/dJ8Vn2kd Google Cloud: 🧊 https://lnkd.in/dg8cwvpa Flask: 🧊https://lnkd.in/dtN8niDC Flask Project: 🧊 https://lnkd.in/dewZ3tTZ Django: 🧊https://lnkd.in/dTRZ8y_Z Follow Arti Yadav for more such content!!!! #datascience #datascienceroadmap #datascience
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❌ Nothing can last forever 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/gaX7kaur <>. Google Data Analytics: 🔺 https://lnkd.in/gnFbzF6x 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/gt86NcUS 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/gNM6ydrN R language: https://lnkd.in/gbVF7e4T SQL: https://lnkd.in/gJ3thah9 MongoDB: https://lnkd.in/gtQj2i2u 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/gkjBQnvA Statistics: https://lnkd.in/gwuxiRDn 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/gzTqf_hE 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/gi-hKbrn 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/g85xkDW2 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/gsvVCx_V Google Cloud: https://lnkd.in/g6QVGxGg Flask: https://lnkd.in/gxadaxFZ Flask Project: https://lnkd.in/gdAtz9sa Django: https://lnkd.in/gFHTHMiu #datascience #python ##programming
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❌ Nothing can last forever 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/gaX7kaur <>. Google Data Analytics: 🔺 https://lnkd.in/gnFbzF6x 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/gt86NcUS 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/gNM6ydrN R language: https://lnkd.in/gbVF7e4T SQL: https://lnkd.in/gJ3thah9 MongoDB: https://lnkd.in/gtQj2i2u 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/gkjBQnvA Statistics: https://lnkd.in/gwuxiRDn 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/gzTqf_hE 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/gi-hKbrn 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/g85xkDW2 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/gsvVCx_V Google Cloud: https://lnkd.in/g6QVGxGg Flask: https://lnkd.in/gxadaxFZ Flask Project: https://lnkd.in/gdAtz9sa Django: https://lnkd.in/gFHTHMiu #datascience #python ##programming
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❌ Nothing can last forever 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/gUt76Eki <>. Google Data Analytics: 🔺 https://lnkd.in/gaN9SjKw 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/gP3rT2Nn 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/gtWYzyuy R language: https://lnkd.in/gQq96zHN SQL: https://lnkd.in/gRiVvB2Y MongoDB: https://lnkd.in/gmxTQ8Gn 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/gQ-ffTUd Statistics: https://lnkd.in/g_cFdH8h 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/g5d_pA42 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/gXqgeTA2 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/gVe2UZ9d 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/gKh6wSsd Google Cloud: https://lnkd.in/gP_9WMCz Flask: https://lnkd.in/gdgi46dU Flask Project: https://lnkd.in/g-DGy8aF Django: https://lnkd.in/gdhWewRm #datascience #python ##programming #remotejobs #learning
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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 about IBM, Deep Learning and Google: Check them out! No Prerequisites required ✅ 🔹 7000+ Courses Access : https://lnkd.in/g36wvRfU <>. Google Data Analytics: 🔺https://lnkd.in/gD4uaKWu 𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: https://lnkd.in/gHZ6enuR 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/gDR3iE2c R language: https://lnkd.in/gSADQ-Sz SQL: https://lnkd.in/gwrbuvJu MongoDB: https://lnkd.in/g67sa__q 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/gPEYEWJm Statistics: https://lnkd.in/gg7nDs3W 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/gJqdpHgE 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/gshmAXCY 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/gRGixbMq 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/gyGNZUit Google Cloud: https://lnkd.in/gaN59bNA Flask: https://lnkd.in/gT2ZS3CS Flask Project: https://lnkd.in/gptA6-3j Django: https://lnkd.in/gkQZdhu4 Happy Learning !!! Kindly Repost, so that it reaches a wider audience. #datascience #datascienceroadmap #sql #dataanalytics #python
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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/dj4BPN7C <>. Google Data Analytics: 🔺https://lnkd.in/d75gurYD 📌𝐌𝐚𝐭𝐡𝐞𝐦𝐚𝐭𝐢𝐜𝐬: - Learn the basics of linear algebra, calculus, and Understand advanced concepts. Mathematics: 🧊 https://lnkd.in/dWerQU2z 📌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/dVXmehyD R language: 🧊 https://lnkd.in/dcPD64QX SQL: 🧊https://lnkd.in/dqdN2Km5 MongoDB: 🧊 https://lnkd.in/dQRBMAuj 📌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/dA4WQiSM Statistics: 🧊 https://lnkd.in/dqe5BiWW 📌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/dqWJzVZY 📌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/dbisy3En 📌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/d3hArpnD 📌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/dJ8Vn2kd Google Cloud: 🧊 https://lnkd.in/dg8cwvpa Flask: 🧊https://lnkd.in/dtN8niDC Flask Project: 🧊 https://lnkd.in/dewZ3tTZ Django: 🧊https://lnkd.in/dTRZ8y_Z Follow Arti Yadav for more such content!!!! #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/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 PDF credits : respective owner. #datascience #datascienceroadmap #datascience #pyton #sql #django
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